Alternative Ways to Measure Recreation Values by the Travel Cost Method

Abstract

The travel cost method is widely used for estimating the economic value of outdoor recreation services. Much early research was empirical applications of the Hotelling-Clawson model (Brown, Singh, Castle; Clawson; Clawson and Knetsch; Trice and Wood). Recently, model specification and functional form problems have attracted greater attention (Allen, Stevens, Barrett; Burt and Brewer; Cesario and Knetsch; Gum and Martin; Smith 1975b; Ziemer, Musser, Hill). A major focus of attention is estimating the recreation participation equation (often called step one of the travel cost method). It measures participation in an activity based on travel costs and other explanatory variables. However, misspecification of this equation is only one possible source of inaccuracy. The procedure for estimating consumer surplus once the participation equation has been derived also can affect the values derived from recreation demand analysis. This paper considers how alternative ways to estimate economic value from participation equations can affect travel cost study results. Empirical study of the economic value of the St. Lawrence River-eastern Lake Ontario bass fishery in New York illustrates the point. The underlying theory of the travel cost method comes from neoclassical demand theory. Demand equations are derived for an outdoor recreation activity by observing how individuals respond to various costs of travel to use the resource. The net economic value (NEV) of the resource in its current use is the amount that users would be willing to pay in excess of their actual expenditures. This is the sum of the users' consumer surplus (Knetsch, Smith 1975a). Assuming that any net user benefits are associated with the recreation site itself rather than the trip, this value represents the net economic value of the recreation resource (Brown, Singh, Castle; Dwyer, Kelly, Bowes). Empirical applications of the travel cost method use visitation data from points of origin at various distances from the site. The traditional approach uses distance zones as units of observation. The quantity variable (visitation rate) is the expected participation rate for a representative individual from a particular origin zone.' Observations of individuals rather than zone averages generally will lead to efficiency gains in estimating the travel cost coefficient and other parameters (Brown and Nawas). The second step is to derive the implied demand for and economic value of the resource from the participation equation. Several methods have been used. One calculates the site's economic value as the area under an aggregate demand curve for the site (Cesario and Knetsch; Grubb and Goodwin; Knetsch, Brown, Hansen). Another method uses the participation equation to derive a demand curve and economic value for the site from each origin. Then aggregation across all origins measures the site's total economic value (McConnell and Norton). This study compares these methods for estimating recreation demand curves and economic value.