Estimation of average and incremental net economic values of Oregon ocean sport-caught salmon : an aggregated travel cost approach Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/7d278w396

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  • The main objective of this study was to estimate the demand for and value of Oregon ocean sport-caught salmon fishery. The primary technique employed to estimate the recreational demand was an aggregated zone average travel cost method (TCM). The willingness of an angler to pay was deduced from the estimated demand for recreational fishing. The concept of consumers' surplus was used in conjunction with the travel-cost based demand functions to estimate the net economic value of Oregon ocean sport-caught salmon. The net economic value computed for the pooled data from all ten ports was found to be about $6.4 million. This value was calculated based on the total travel cost per mile of one-way distance equal to 72 cents. The regional travel cost method (RTCM) was developed to measure the effects of substitutes and quality variables in the travel cost model. A system of a linear demand equations for the six larger ports was estimated by the seemingly unrelated regression equation (SURE) method. The substitute distances as proxies for substitute prices were found to be insignificant for this model. Likewise, attempts to include substitute distances using indexes constructed by the Principal Component analysis failed to give significant results, with the exception of Garibaldi and Brookings. The total net economic value for the regional travel cost model estimated by SURE was $9.1 million. The incremental value per coho equivalent was also assessed by using the relationship between catch and effort per month by port. The coho equivalent was constructed on the basis of average weights of the commercial salmon catch, which was roughly two coho to one chinook salmon. The weighted average incremental value per coho and chinook was found to be $23.46 and $43.17, respectively. These values were about 50 percent of their respective average values. A total of 66 out of 234 distance zones created had zero values. Tobit analysis was employed to efficiently estimate the recreational demand from this kind of data. From the estimated demand function, a net economic value of about $12.7 million was obtained. This value was higher than those estimated by the SURE method and the OLS in the simple model. It should be noted that all the above value estimates were based upon demand models that were not consistent with the theory of consumer demand. However, a theoretically consistent system of demand equations was estimated and presented in Appendix D. This model fitted the data better than the other models and should give more accurate estimates of consumer surplus.
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