© International Review on Public and Non Profit Marketing, vol. 2, nº 1 (June 2005), pp. 73-84. 73

ESTIMATION OF MEDIAN WILLINGNESS TO PAY FOR A SYSTEM OF RECREATION AREAS Kimberly Rollins*

Diana Elena Dumitras**

ABSTRACT:

This study provides information about people’s valuation of recreational user days on public lands. The contingent valuation method is used with a random paired dichotomous choice question format. A bivariate probit model is utilized to estimate parameters of a willingness to pay function, which is used to calculate welfare measures associated with trips to three different sites and eight diverse recreational activities.

The results indicate that recreational values vary by site and by activity. Per day user values range from $ 12.15 CAN per day for trips for general rest and relaxation at a lake area popular for weekend visits to $ 35.65 CAN per day for white water canoeing on a wilderness river. Values on a per trip basis range from $ 258.11 CAN for hunting to $ 97.87 CAN for weekend lake canoeing. Key Words:

Contingent valuation; willingness to pay; recreation; dichotomous choice; bivariate probit; non-market valuation.

* Department of Resource Economics – University of Nevada, Reno. Mail Stop 204, Reno, Nevada 89557-0105 (USA). E-mail: krollins@cabnr.unr.edu ** Department of Resource Economics – University of Nevada, Reno. Mail Stop 204, Reno, Nevada 89557-0105 (USA). E-mail: dea_d_ro@yahoo.com Authors gratefully acknowledge Ontario Parks and the Ontario Ministry of Natural Resources, for the resources provided for this study. Received: February 2005. Accepted: April 2005.

74 Kimberly Rollins and Diana Elena Dumitras

1. INTRODUCTION:

Changes in population demographics and in preferences for leisure activities have contributed to an increasing demand for recreational use of public lands in many parts of the world (see, for example, Foot, 1989/90 and 2004; The Economist, 1997; Bowler, English and Cordell, 1999; Nickerson, 2000; and Smailes and Smith, 2001). Public land managers have a variety of options in addressing these changes: use patterns at existing recreational areas can be measured and evaluated to determine whether current management strategies on these lands should be revised in order to generate greater value to recreational users; areas not previously managed for recreational uses can be developed for recreation, thus adding capacity on public lands. In either case, useful management information would include estimates of the demand for recreation on existing and new areas, and how user benefits vary with site characteristics, recreational uses, and user characteristics.

Because user fees for public lands access generally do not reflect market forces, benefits from recreational use of public lands are typically estimated using non-market valuation methods (Freeman, 1993; Loomis, 1993). This study uses contingent valuation to measure the benefits of three recreation areas in terms of Willingness To Pay (WTP) for trips by different user groups and different on-site activities in Ontario (Canada). The three sites were chosen to be representative of site characteristics and recreational opportunities that are similar to those expected at six other sites yet to be developed for recreational use. A goal of the study is to determine whether per trip values vary by site characteristics and activities. The estimated values can be used to understand how benefits are generated at existing sites and to provide information for developing the new areas.

The contingent valuation method has been the focus of intense study for several decades, resulting in a number of works describing theory and methods in relation to valuation of natural resources, environmental amenities and public goods (see, for example, Freeman, 1993; Bateman and Willis, 1999; and Champ, Boyle and Brown, 2003). Contingent valuation requires data collection using survey methods that directly elicit people’s valuation of public goods and services by determining what they would be willing to pay, or to accept in compensation, for specified changes in the quality or quantity of a public good (Mitchell and Carson, 1993). Responses are used as data in econometric models to estimate individual benefits, which can then be aggregated over the relevant population of recreational users in a given year to calculate annual benefits, or welfare measures.

Question design is critical to overall results. The most popular valuation question format is the dichotomous choice (yes / no response) format, which asks individuals whether they would pay a specific dollar amount in order to obtain the good in question. The term “bid design” refers to the distribution of dollar amounts offered individuals over the sample. Previous research demonstrates that the efficiency of welfare estimates can be improved by: a) optimizing over the distribution of bid amounts offered to respondents (Kanninen, 1993; Rollins, 1997; Dumitras, 2004); and b) using valuation formats with follow-up questions (Hanemann, Loomis and Kanninen, 1991; Cameron and Quiggin, 1994). A follow-up question is a second dichotomous choice question in which the dollar amount presented is different from the first question.

The standard dichotomous choice approach that uses a follow-up question is the Double Bounded (DB) dichotomous choice format in which the second offer amount

Estimation of Median Willingness to Pay for a System of Recreation Areas 75

presented to the respondent is conditional on the respondent’s response to the first amount. A person indicating that they would not pay the amount they are presented with first would subsequently be presented with a lower amount for the follow-up question; and a person who responded in the affirmative would receive a higher second bid.

In contrast, this study poses valuation questions using a Random Paired (RP) dichotomous choice format, in which respondents are asked two valuation questions regarding their willingness to pay for a good (a recreation trip similar to the one they were on when they received their questionnaire). The bid amounts for each question are randomly drawn from the same distribution. Thus, while they are different, the second is not conditional on the response to the first. The order of the two dollar amounts is random, so half progress from high to low and the other half from low to high.

In terms of elicitation format, the DB dichotomous choice format is well-suited for in-person survey methods (phone or face-to-face), or interactive computer-based methods in which the second offer amount can be conditioned on the response to the first. Mail surveys, however, are not as well-suited to this conditional format since the respondent sees all bid amounts being offered. Thus, a single question dichotomous choice format in which there is no follow up, or the RP approach for including a follow-up, are better suited for mail surveys.

The DB dichotomous choice format would be expected to be more efficient than the RP dichotomous choice format. The inclusion of a follow-up question per respondent narrows the boundaries of WTP estimates, thereby improving informational content of each observation (Hanemann, Loomis and Kanninen, 1991). While a single dichotomous choice question results in one of two outcomes, the pairs of answers to follow-up formats result in one of four outcomes per respondent: “yes-yes”, “no-no”, “yes-no”, and “no-yes”. A “yes-yes” response pair provides a lower bound as the higher of the two dollar bids with income being the upper bound. A “no-no” pair provides $ 0 as the lower bound and the lower of the two bids as the upper bound. In general, “yes-no” and “no-yes” pairs provide narrower bounds on individual WTP, and hence contribute more information to the estimation of welfare measures. Because the second bid amount in the DB format is conditioned on the response to the first, this approach is likely to result in a larger proportion of “yes-no” and “no-yes” outcomes than would be expected with both dollar amounts being randomly assigned. The RP method results in a number of “yes–yes” responses in which the first “yes” is followed by a lower bid amount, and vice versa. These pairs result in no more information than would a single dichotomous choice question based on the first amount.

The increased statistical efficiency of the DB over the RP approach is partly an empirical issue, depending on the underlying distribution of WTP and on the bid design strategy used for the RP and DB approaches. However, given the difficulties of implementing the DB approach in mail questionnaires, the RP approach for a mail questionnaire would be more efficient than a single dichotomous choice question approach. This study uses the random paired dichotomous choice format in a mail-back questionnaire. We are unaware of other published studies that have used the RP approach.

A bivariate probit model is used to estimate the probability that individuals would be willing to pay a specified additional dollar amount to take the same trip (same site, activity, length, conditions) as they experienced when they were given the questionnaire. The data

76 Kimberly Rollins and Diana Elena Dumitras

include trips to a variety of sites, and with a variety of trip and individual characteristics. Estimation procedures provide information on how these differences affect the probability of a “yes” response to a given increase in dollar cost. The estimated probabilities are in turn used to calculate welfare measures as described below. 2. EMPIRICAL MODEL:

The empirical model is based on random utility maximization, in which utility is represented as the sum of systematic and random components (Hanemann, 1984). The random utility function is represented as equation [1]:

U (j, y, s) = V (j, y, s) + ε [1]

where: U = unobservable indirect utility; j = vector of goods and services; y = income; s = other individual characteristics; V = systematic component of utility; ε = random component.

Thus, the unobservable indirect utility depends on both a systematic and a random component of utility, meanwhile individual preferences may be affected by income and other individual characteristics. A utility maximizing individual will accept an offer for an alternative trip j1 rather than trip j0 at an additional cost P if utility is at least as great or greater, that is:

V1 (j1, y-P, s) + ε1 ≥ V0 (j0, y-P, s) + ε0 [2]

where: P = additional cost of trip 1 over trip 0; jk = recreation trip k, where k = 0, 1.

Otherwise (that is, in case U1 < U0), the individual will refuse such an additional cost.

Random Utility Models (RUMs) assume that individuals know which choice maximizes utility: from the respondent’s perspective, the outcome is deterministic. The researcher, however, cannot observe everything that affects individual utility, so the outcome appears stochastic. Therefore the individual’s response to a single dichotomous choice question is modeled as a random variable with the probability of a “yes” response given by:

P1 = Prob (yes) = Prob [V1 (j1, y-P, s) + ε1 ≥ V0 (j0, y-P, s) + ε0] = Fη (η, ∆V) [3]

where: P1 = Prob (yes), probability of “yes” response; P0 = Prob (no) = 1 – Prob (yes), probability of “no” response; η = ε0 – ε1; Fη = cumulative density function of η.

According to [3], a person will respond with a “yes” if the change in utility obtained by acquiring the alternative trip at the given price P is greater than zero. A “yes” response to a given dollar amount implies a “yes” response to any smaller dollar amount. The maximum willingness to pay for the good is found by setting ∆V equal to zero and solving for P. When the cumulative density function is assumed to be standard normal, the probability of a “yes” response corresponds to a standard probit model.

Estimation of Median Willingness to Pay for a System of Recreation Areas 77

The random paired data include two observations per individual, as a replication of equation [2], which differ in terms of the dollar cost of the trip, P1 and P2:

V1 (j1, y-P1, s) + ε1 ≥ V0 (j0, y, s) + ε0

V2 (j1, y-P2, s) + ε2 ≥ V0 (j0, y, s) + ε0

[4]

A bivariate probit model is used for estimation to allow for correlation among responses by individual. The general expression for the bivariate probit model is given by Greene (2003):

y*i1 = βx’

i + εi1 y1 = 1 if y*1 > 0, 0 otherwise

y*i2 = βx’

i + εi2 y1 = 1 if y*2 > 0, 0 otherwise

[5]

where: i = subscript that indicates the individual respondent; 1, 2 = subscript that indicates the first and second response per individual; y*

it = unobserved latent variable (where t = 1, 2); yit = observed random variable; x’

i = vector of explanatory variables; β = vector of coefficients.

The error structure is:

E (ε1) = E (ε2) = 0

Var (ε1) = Var (ε2) = 1

Cov (ε1, ε2) = ρ

[6]

The covariance between responses is indicated by ρ. Under the null hypotheses that ρ = 0, the errors are unrelated and the model is a probit in which all equations are independent. A high ρ indicates that the bivariate model is necessary to correct for correlation among the pairs of responses per individual. The model is estimated using maximum likelihood (see Greene –2003– for derivation of the likelihood function).

The coefficients from the estimation are applied to the data to predict the probability that a representative individual would be willing to take the same trip and participate in the same recreational activities if it were available at a higher cost. The median maximum WTP is the calculated dollar amount that is associated with a 50 % probability of a “yes” response (Hanemann, 1984; Maddala, 1983).

A set of dummy variables and cross-terms is incorporated into the model to test whether the maximum WTP differs by site and type of recreational activity. Thus, for a model in which there are three sites, there are three bid amount variables: xsite 1, xsite 2, and xsite 3. The value of each of these depends on to which of the sites the observation applies: the value for xsite 1 = 0 if the observation is from site 2 or 3; and xsite 1 = dollar bid value if the observation is from site 1. Parametric tests then determine whether the three individual bid coefficients are different. If they are different, the WTP estimates would be calculated for each site using the corresponding parameter estimate.

Similarly, differences in WTP by recreational activity are tested for by including dummy variables for activities. WTP for activity may also differ by site; and some activities may not be important or present at some sites, while being a primary purpose for trips at

78 Kimberly Rollins and Diana Elena Dumitras

other sites. Thus, activity dummy variables would take on values of either 0 or 1, depending on the site and activity corresponding to each observation. In models where a constant term is used, one activity dummy is omitted, and the difference in WTP for that activity is indicated by the constant term.

A variable for trip length, measured in days is included since WTP per trip would be expected to vary by the length of trip. Separate trip length variables by site can be included to test for corresponding differences in WTP. Finally, other variables that describe variation in participant characteristics can be incorporated in to the model to test for differences in WTP by activity, site and demographic characteristics, such as income, age, number of people in the group, and the presence of children.

The estimated econometric results provide a parameterized model describing how WTP varies by activity, trip length, site characteristics, and demographic characteristics. The model can be used to calculate WTP by trip for the actual sites from which data were obtained. In addition, the model can be used, with caution, to predict WTP per trip for other recreational sites by applying estimated parameters to alternative site data. This process, known as benefits transfer, is well documented elsewhere (see, for example, Brouwer and Spaninks, 1999; and Bergstrom and De Civita, 1999). While an actual benefits transfer to other sites is beyond the scope of this paper, the study described here was developed to provide the basis for future benefits transfers to other sites in Ontario.

Site characteristics and data collection:

This study focuses on three recreation areas in Ontario (Canada): Killarney Provincial Park, Kawartha Highlands, and Spanish River Valley. The areas differ in site characteristics and recreational activities supported. Killarney Provincial Park is a wilderness canoe area with many lakes and connecting waterways, rugged terrain with granite hills and spectacular views. Because the water is relatively calm, Killarney is attractive to beginner and intermediate canoeists and families with children. Group numbers and sizes are limited by quota, and boats with motors are not permitted. The park maintains camping areas accessible by car and a system of hiking trails.

Kawartha Highlands is within two hours of large urban populations, is a popular weekend getaway, has neither user quotas nor restrictions on motor boat use, and has numerous private cottages, roads and campgrounds interspersed with the public lands. The terrain is flat with interconnected lakes and calm waterways. Public infrastructure includes ample road access, public parking and boat ramps. The area does not feature public hiking trails or car-camping areas, as does Killarney. Kawartha is unique in having a number of private hunting camps on public lands. While it is no longer possible to create new private leases on public lands in Ontario for hunting, these camps were leased many years ago under long term agreements. Hunting is not legal in Killarney and not as common an activity at Spanish River.

The Spanish River is an intermediate to advanced white water canoeing destination, with access limited by its remote location. Canoeists typically put in up river with the average trip progressing over 5 days through a varied landscape that features canyons and high quality white water runs. A number of private companies provide canoes, and arrange transportation by train up river. There are no car camping areas, nor public hiking trails.

Estimation of Median Willingness to Pay for a System of Recreation Areas 79

Cottages located on nearby private lands are destinations for groups of people who can make extended visits to this remote area.

The three sites offer a variety of activities, such as canoeing, boating, hiking and camping. However, due to differing site characteristics, the qualities of trip experiences and activities would be expected to vary considerably. We hypothesize that WTP per trip would also vary by activity and site.

Data were collected by a questionnaire distributed to a random sample of visitors as they started their trips at each site. Participants were asked to provide addresses and basic demographic information on-site, and asked to complete their questionnaires after completing their trips. Those who did not respond after two weeks were mailed a reminder. Two weeks later remaining non-respondents were mailed a replacement questionnaire. The questionnaire was piloted in 2003 to determine first round estimates of the distribution of WTP as described in Rollins (1997). Data were then collected over the entire season from June until October, 2004. Since it is possible that some activities or user types might be more or less abundant during different parts of the recreational season, sampling over the entire season was done to ensure a representative sample of activities and user characteristics. The overall response rate of the 2004 study was 63.46 %, resulting in 1818 usable surveys. Table 1 indicates numbers of survey respondents taking part in selected activities and trip lengths for the three areas.

Respondents were asked to indicate the primary activity they participated in while on their trip and length of their trip. The activity category rest and relaxation was included to describe a primary activity for those who took part in a number of different activities, none of which was the primary purpose of the trip. Respondents were also asked where they stayed while on overnight trips. While the majority stayed in tents or campers, a large number of Kawartha visitors stayed at private cottages (either owned by themselves, friends or family, or rented from others). Table 1. Number of respondents and trip length by activity and site.

Kawartha Highlands Killarney Park Spanish River Activity N. Resp. A.T.L. (d) N. Resp. A.T.L. (d) N. Resp. A.T.L. (d)

Canoeing and fishing 289 3.6 560 4.4 70 5.9 Kayaking 15 1.9 39 3.9 3 3.7 Hunting 47 10.6 0 ----- 3 5.0 Rest and relaxation 160 12.1 102 3.4 22 11.8 Hiking 7 3.7 258 3.6 0 ----- Backpacking 1 3.0 12 4.1 1 1.0 Boating 13 9.6 0 ----- 0 ----- Car camping 1 2.0 97 4.1 0 ----- Other* 17 8.5 8 1.1 3 14.0

Total: 550 6.7 1076 4.0 112 7.2 Private Cottage Accom. 261 12.6 29 3.4 34 11.0 N. Resp.: Number of Respondents; A.T.L. (d): Average Trip Length (days); Private Cottage. Accom.: Number of total respondents who listed “Private Cottage” as Accomodation type. * Includes ATV use, nature photography, painting, scuba diving, swimming, and picnicking.

80 Kimberly Rollins and Diana Elena Dumitras

3. RESULTS AND DISCUSSION:

Two models are estimated. The first model results in the coefficients necessary to calculate the median WTP per trip, and to test for differences among the sites. The dependent variable is the yes / no response to the trip valuation question. Independent variables include dollar bid amounts set up as cross terms for each site, thus giving separate coefficients by site. Other independent variables that are allowed to vary by site are income per household member and duration of trip. The presence of children under the age of 14 is a dummy variable that takes on the value of 0 if there are no children and a 1 if the group includes children. Model 1 results are presented in Table 2.

Because the models are estimated using maximum likelihood, coefficients indicate the contributions of each variable to the likelihood of a “yes” response. Thus, positive coefficients suggest that increases in the variable values increase the probability of a “yes” response and negative values indicate decreases in the probability of a “yes” response. The numerical values of the coefficients provide the parameters of the equation by which predicted individual WTP is calculated. The high value for ρ indicates that the bivariate probit specification is preferable to a probit model that would otherwise treat responses from each individual as independent.

Preliminary results indicated that the dummy for the presence of children under 14 was not significant for either Kawartha Highlands or Spanish River. That is, the WTP for a trip for these sites did not vary depending on the presence or absence of children in these groups. However, the coefficient is positive and significant for Killarney, suggesting that WTP per trip is higher for groups that include children. Thus, Model 1 retains this dummy variable only for Killarney.

The coefficients on income for Killarney and the Spanish River are positive and significant, suggesting that WTP increases with income for these sites. WTP does not appear to be sensitive to income for Kawartha trips, however. All other coefficients significant with signs as expected.

WTP decreases with trip cost. The coefficient for the increase in trip cost (the bid amount) variable for Killarney is significantly different from the other two sites. The coefficients for duration of the trip variable are significant at the 1 % level and different across the three sites. Since the coefficients on trip costs are significantly different by site, it not surprising that the coefficients on trip length also vary by park. Table 2. Estimation results per trip by site for all users.

Variables Kawartha Highlands* Killarney Park* Spanish River*

Increase in trip cost -0.0267** (0.0031) -0.0507** (0.0061) -0.0365** (0.0062) Duration 0.1538** (0.0208) 0.6167** (0.0753) 0.3982** (0.1409) Income 0.0065 (0.0042) 0.0387** (0.0061) 0.0813** (0.0247) Children under 14 ----- ----- 0.8760** (0.2472) ----- ----- Constant 2.1884** (0.3587) 2.1884** (0.3587) 2.1884** (0.3587)

Log likelihood: -1548.1142 ρ: 0.9424 Nº of observations: 3031 Nº of groups: 1524 * Standard errors shown in parentheses. ** Significant at 1 % level or above.

Estimation of Median Willingness to Pay for a System of Recreation Areas 81

Figure 1. Willingness to pay per trip by site.

The probability curves in Figure 1 are calculated from the sample data and the estimated coefficients from Model 1, where the probability of a “yes” is written as shown:

1 Prob (yes) = 1 + exp [–(βx’i)]

[7]

Equation [7] corresponds to a logit equation, which can be used to calculate probabilities using estimated coefficients from a probit equation, following Maddala (1983). The horizontal axis is the increase in trip costs (bid amount) and the vertical axis represents the estimated probability of a “yes” response. Thus, the median WTP is the dollar amount that corresponds to a 50 % probability that a person will respond “yes”. Equation [7] is applied to coefficients and data for each site, so that Figure 1 illustrates the differences between sites. Spanish River Valley trip values are higher over all. This may be true because there are fewer alternative locations for white water canoeing, and this is a highly valued activity in a unique location. The WTP per trip curves for Kawartha and Killarney intersect at about 50 % probability of “yes”, indicating that median WTP per trip values are similar; but at the margins the WTP differs slightly among these sites. Figure 1 refers to a representative individual based on a random sample from each of the three sites. If the Killarney data and equations were separated by groups with and without children, the WTP curve for the groups with children would be greater, that is, more to the right, than the children groups without, due to the positive coefficient on the children dummy variable for Killarney.

Model 2 includes dummy variables to test for differences in WTP by recreational activity, as shown in Table 3. The dummy variables take on a value of 1 if the participant indicated that this was a primary trip activity and 0 otherwise. Since the primary purpose of Spanish River trips is white water canoeing, Model 1 results are assumed to apply to this activity alone and Spanish River observations were omitted from Model 2. The constant was omitted; the dummies for activities have the role of the constant. While the majority of respondents indicated that they participated in one main activity, a number of people who participated in multiple activities selected rest and relaxation as their main activity.

82 Kimberly Rollins and Diana Elena Dumitras

Table 3. Estimation results for determining WTP per activity by site.

Variables Kawartha Highlands* Killarney Park*

Increase in trip cost -0.0295** (0.0038) -0.0498** (0.0067) Duration 0.1431** (0.0282) 0.5867** (0.0754) Income ----- ----- 0.0359** (0.0054) Children under 14 ----- ----- 0.9493** (0.3027) Canoeing 2.3663** (0.4501) 2.3663** (0.4501) Kayaking ----- ----- 2.7248** (1.1993) Boating 2.7328** (0.7062) ----- ----- Hunting 6.0906** (0.8848) ----- ----- Hiking ----- ----- 2.3290** (0.5829) Rest and relaxation 2.6108** (0.5156) 2.6108** (0.5156) Car camping ----- ----- 1.4911** (0.4704) Backpacking ----- ----- 3.4743** (1.2233)

Log likelihood: -1464.3019 ρ: 0.9403 Nº of observ.: 2859 Nº of groups: 1438 * Standard errors shown in parentheses. ** Significant at 1 % level or above.

Kayaking, hiking, backpacking and car camping do not occur often enough in the data for Kawartha Highlands to be included as dummy variables for that site. Similarly, hunting and boating do not occur often enough for inclusion as dummies for Killarney. While the coefficients on the dummy variables for rest and relaxation and for canoeing at the two sites are significant at the 1 % level, a preliminary model indicated that they are not significantly different among the two sites, thus these are constrained to be the same in Model 2.

Table 4 presents the calculated median WTP per trip and main activity for all above estimated models. While Model 1 results indicate that the children under 14 variable is significant for Killarney, the difference in WTP between the groups with and without children under the age of 14 is $ 3.26. Thus, the calculation of median WTP for activities in Table 4 refers to all groups at Killarney. The first row of Table 4 gives the WTP per trip for each site, calculated from Model 1 results. Table 4. Willingness to pay per trip and per day for sites and activities.

Kawartha Highlands Killarney Park Spanish River Model WTP/site/ trip category per trip per day per trip per day per trip per day

1 Average/trip $ 126.28 $ 18.85 $ 121.99 $ 30.50 $ 210.33 $ 29.21

2 Canoeing $ 97.87 $ 27.19 $ 127.35 $ 28.94 $ 210.33 $ 35.65 Kayaking ----- ----- $ 134.61 $ 34.52 ----- ----- Boating $ 139.24 $ 14.50 ----- ----- ----- ----- Hunting $ 258.11 $ 24.35 ----- ----- ----- ----- Rest and Relax. $ 147.04 $ 12.15 $ 121.67 $ 35.79 $ 210.33 $ 17.82 Hiking ----- ----- $ 116.53 $ 32.37 ----- ----- Car camping ----- ----- $ 105.34 $ 25.21 ----- ----- Backpacking ----- ----- $ 134.99 $ 32.92 ----- -----

Estimation of Median Willingness to Pay for a System of Recreation Areas 83

WTP per trip differs among sites, as expected because the sites have different characteristics and user groups. Dividing WTP by trip length, for a rough indication of average per day WTP, these results indicate that people are willing to pay on average $ 18.85 per day for trips to Kawartha, $ 30.50 per day for trips to Killarney and $ 29.21 per day for trips at Spanish River. The median WTP per day for a canoeing trip are $ 27.19, $ 28.94 and $ 35.65 for Kawartha, Killarney and Spanish River. Canoeing at Spanish River is unique because it has high-quality whitewater.

People are willing to pay on average $ 34.52 per day for kayaking trips at Killarney and for car camping trips $ 25.21. Hiking and backpacking trips at Killarney have similar median WTP per day. Hunting is an important recreational activity at hunting camps at Kawartha, with hunters willing to pay on average $ 258.11 per trip (or an average of $ 24.35 per day). Kawartha is known for recreational boating, with visitors taking trips on average of 9 days and being willing to pay on average $ 14.50 per day.

The median WTP for rest and relaxation trips differ among the sites, the value being significantly higher at Killarney. This site is tourist oriented. People tend to stay on average 3 days for rest and relaxation trips at Killarney and are willing to pay on average almost twice as much as for the other two sites for a relaxation trip, where the trips average 12 days in length.

Using these results for benefit transfers to other sites:

The WTP results presented in Table 3 and Figure 1 are calculated from estimated coefficients applied to actual data from each site. A benefits transfer exercise whereby these results are extended to predict values for sites that were not included in the survey sample could be conducted by using these coefficients with expected means of the respective variables for other sites that may be similar in characteristics and recreational opportunities. Thus a rough estimate of WTP for another site that shares similarities in site characteristics with Killarney and offers opportunities for canoeing and camping could be calculated by using expected trip duration, average income, proportion of groups with children under 14, and expected numbers of trips to the new site, with coefficients from Killarney Model 2 results. 4. CONCLUSIONS:

The current study contributes an effective method for generating useful information for managing public lands for recreation. The study presents methodologies that are easily generalized to other cases in which mail-back surveys can be conducted over multiple sites and recreational activities. Estimating WTP for multiple sites and activities allows for parametric testing of whether WTP varies among sites and activities. Trip values for Kawartha Highlands and Killarney Park are more similar, Spanish River trip values are higher. Several user activities are identified as having different values within and among the sites.

The study also gives evidence that the Random Paired (RP) dichotomous choice format and the bivariate probit model is an efficient framework in estimating the welfare measures for recreation trips, and can be employed in mail-back questionnaires where one-on-one question methods that allow for the more common Double Bounded (DB) method is not possible.

84 Kimberly Rollins and Diana Elena Dumitras

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