Non-Market Goods - Revealed Preferences - Travel Cost Method
Methodology  -  Lake State Examples - Other Examples         
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Methodology:

Ribaudo, M. O. and D. J. Epp. 1984. "The Importance of Sample Discrimination in Using the Travel Cost Method to Estimate the Benefits of Improved Water Quality." Land Economics 60(4):397-403.

This paper presents an application of the travel cost method to estimate the value of a recreation site with some hypothetical improvement in water quality. Particular attention is paid to the appropriate survey method. Simply surveying current users with contingent valuation questions would not capture the values of users who may have stopped using the site due to its current poor condition. It is hypothesized that these two groups will value water quality improvements differently and valuation result from one group cannot be inferred for the other. Ordinary least squares regression was used to estimate the demand equations for each group and they were found to be significantly different.

Dwyer, J. F., J. R. Kelly and M. D. Bowes. 1977. Improved Procedures for Valuation of the Contribution of Recreation to National Economic Development. Research Report 128. Urbana, IL: Water Resources Center, University of Illinois.

This report written in the context of national economic development, provides a lengthy description of two techniques commonly used to determine the value of recreation resources by calculating consumer willingness to pay: a straightforward survey method and the travel cost method. This report advocates strongly for the use of the travel cost method.

Lake States Examples:

Murray, C. and B. Sohngen. 2001. "Valuing Water Quality Advisories and Beach Amenities." Water Resources Research 37(10):2583-2590.

This paper present estimates of the value of reducing beach advisories along Lake Erie's shoreline in Ohio. Using a travel cost model, the seasonal benefits of reducing one advisory is estimated. A random utility model is linked to a Poisson model that predicts annual trips based on individual willingness to pay and other individual characteristics. Individuals who use the media in advance of trips gain less, approximately $24 per year, while those who use only signs posted at the beach would gain more, $38 per year.

Upneja, A., E. L. Shaffer, W. Seo and J. Yoon. 2001. "Economic Benefits of Sport Fishing and Angler Wildlife Watching in Pennsylvania." Journal of Travel Research 40(August):68-78.

This article answers two major policy questions about the economic benefits of sport fishing in Pennsylvania: what is the annual value of Pennsylvania's sport fishing resources, and what is the annual economic impact from the use of that resource. Data from a mail-based questionnaire with 907 respondents was used to answered these questions using the travel cost method and input-output analysis (IMPLAN). The annual total value of the sport fishing resource was found to be $3.98 billion or about three times the total out-of-pocket expenses. The study found an overall economic impact of sport fishing of 4.75 billion.

Provencher, B. and R. C. Bishop. 1997. "An Estimable Dynamic Model of Recreation Behavior with an Application to Great Lakes Angling." Journal of Environmental Economics and Management 33:107-127.

Travel cost method is widely applied to estimate the economic benefit of nonmarket resources for site-specific recreational activities. This paper develops a dynamic structural model of the decision to visit a recreation site. Compared to the typical static model approach to this problem, a dynamic model allows the analyst to develop a decision problem that looks more like "the real thing". For illustration, the model is applied to the decisions of of fishing club members on the Wisconsin shore of Lake Michigan. The authors conclude that due to the challenges of obtaining appropriate data and some of the limiting assumptions of the model, that this type of model is likely appropriate only in certain circumstances. In many cases the static model will likely yield welfare estimates similar to the dynamic model with much less cost and effort. The relative accuracy of each modeling technique needs more empirical investigation.

Other Examples:

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