Modeling Recreation Demand when the Access Point is Unknown

The task of modeling the recreation demand for geographically large sites, such as rivers and beaches or large parks with multiple entrances, is often challenged by incomplete information regarding the access point used by the individual. Traditionally, analysts have relied upon convenient approximations, defining travel time and travel distances on the basis of the midpoint of a river or beach segment or on the basis of the nearest access point to the site for each individual. In this paper, we instead treat the problem as one of aggregation, drawing upon and generalizing results from the aggregation literature. The resulting model yields a consistent framework for incorporating information on site characteristics and travel costs gathered at a finer level than that used to obtain trip counts. We use a series of Monte Carlo experiments to illustrate the performance of the traditional mid-point and nearest access point approximations. Our results suggest that, while the nearest access point approach provides a relatively good approximation to underlying preferences for a wide range of parameter specifications, use of the midpoint approach to calculating travel cost can lead to significant bias in the travel cost parameter and corresponding welfare calculations. Finally, we use our approach in modeling recreation demand for the major river systems in Iowa using data from the 2009 Iowa Rivers and River Corridors Survey. This paper was supported by Hatch Act and State of Iowa funds. Funding for this project was also provided by the Iowa Department of Natural Resources and the U.S. Environmental Protection Agency’s Science to Achieve Results (STAR) program. Although the research described in the article has been funded in part by the U.S. Environmental Protection Agency through grant R83426001, it has not been subjected to any EPA review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred. Contact author information: 260 Heady Hall, Department of Economics, Iowa State University, Ames, IA 50011. email: [email protected]. Phone: 515-294-4964