Recreation demand analysis under truncation, overdispersion, and endogenous stratification: an application to Gros Morne National Park

Using on-site survey data from Gros Morne National Park in Newfoundland, this paper estimates and compares several truncated count data models of recreation demand. The selected model accounts not only for the truncated and overdispersed nature of the data but also for endogenous stratification due to the oversampling of avid users. Moreover, the model that allows for a flexible specification of the overdispersion parameter dominates on the basis of goodness of fit. The results are used to estimate the users' value of access to the park.     

Valuation of National Park System Visitation: The Efficient Use of Count Data Models, Meta-Analysis, and Secondary Visitor Survey Data

The National Park Service (NPS) currently manages a large and diverse system of park units nationwide which received an estimated 279 million recreational visits in 2011. This article uses park visitor data collected by the NPS Visitor Services Project to estimate a consistent set of count data travel cost models of park visitor willingness to pay (WTP). Models were estimated using 58 different park unit survey datasets. WTP estimates for these 58 park surveys were used within a meta-regression analysis model to predict average and total WTP for NPS recreational visitation system-wide. Estimated WTP per NPS visit in 2011 averaged $102 system-wide, and ranged across park units from $67 to $288. Total 2011 visitor WTP for the NPS system is estimated at $28.5 billion with a 95% confidence interval of $19.7–$43.1 billion. The estimation of a meta-regression model using consistently collected data and identical specification of visitor WTP models greatly reduces problems common to meta-regression models, including sample selection bias, primary data heterogeneity, and heteroskedasticity, as well as some aspects of panel effects. The article provides the first estimate of total annual NPS visitor WTP within the literature directly based on NPS visitor survey data.     

Estimating the Recreation Demand and Economic Value of Mountain Biking in Moab,Utah: An Application of Count Data Models

This paper reports the results of both standard and truncated count data travel cost demand models for estimating demand for and the economic value to participants in mountain biking in the Moab, Utah, area. The empirical estimates for average trip demand per person per season were 2.25 and 2.53 trips under truncated Poisson and truncated negative binomial models, respectively. Consumer surplus per person per trip for both models was approximately US $585. The total annual use value for mountain biking in the Moab area was US $1.33 million. This value suggests that this recreation has a higher value than most other activities in the area and that public land managers should be aware of the relative value of mountain biking as they make allocation decisions.