current distance and the maximum distance assumed to be relevant 

 for the model . Net economic value for each site is then the 

 population-weighted sum of each zone's net willingness to pay. 



The alternative approach is to calculate a second stage, or 

 site, demand curve from Equation 1. This second stage demand 

 curve relates total trips made to a given site to increases in 

 distance (or travel cost), over and above existing distance (or 

 cost). The area under this curve is also an estimate of net 

 willingness to pay. 



The approach used in this study is direct integration of the 

 first stage demand curve, which is an exact method. The second 

 stage approach involves either an approximation in estimating 

 area (generally a numerical methods approach, such as the 

 trapezoidal approximation, is used) or an approximation in 

 deriving the second stage demand function (through regression 

 analysis, for example). The general equivalence of these two 

 approaches has been demonstrated in the literature (Burt and 

 Brewer, 1971; Menz and Wilton, 1983). 



The major assumption involved in benefit estimation is the 

 choice of the appropriate upper limit of integration. With the 

 double log model, trips per capita asymptotically approach zero 

 as distance approaches infinity. The distance where trips fall 

 close to zero may exceed a site's likely market area, and, in any 

 case, the definition of a limit based on trips (one, "close to 

 zero", etc.) is arbitrary. We have chosen to truncate the 

 second stage demand curve at the highest observed distance in the 

 sample. The equivalent limit for direct integration of the 

 first stage equation is to integrate to the highest observed 



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