Modeling Recreation Demand When the Access Point Is Unknown
针对进入大型休闲区域入口点未知的问题，本文提出基于聚合文献的框架，利用更细粒度数据建模休闲需求，并通过蒙特卡洛实验比较传统中点法和最近入口点法的表现。
Not observing where an individual enters a geographically large recreation area complicates the task of modeling recreation demand. Traditionally, analysts have arbitrarily defined distances on the basis of the midpoint of a river or beach segment or on the basis of the nearest access point. In this article, we draw on the aggregation literature to generate 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 Monte Carlo experiments to illustrate the performance of the traditional midpoint and nearest access point approximations. Our results suggest that, while the nearest access point approach often provides a good approximation to underlying preferences, use of the midpoint approach can lead to significant bias in the travel cost parameter and corresponding welfare calculations. Finally, we use our approach to model recreation demand for the major river systems in Iowa using data from the 2009 Iowa Rivers and River Corridors Survey.