Private Options to Use Public Goods: Exploiting Revealed Preferences to Estimate Environmental Benefits
We develop and apply a new method for estimating the economic benefits of an environmental amenity. The method fits within the household production framework (Becker 1965), and is based upon the notion of estimating the derived demand for a privately traded option to utilize a freely-available public good. In particular, the demand for state fishing licenses is used to infer the benefits of recreational fishing. Using panel data on state fishing license sales and prices for the continental United States over a fifteen-year period, combined with data on substitute prices and demographic variables, a license demand function is estimated with instrumental variable procedures to allow for the potential endogeneity of administered prices. The econometric results lead to estimates of the benefits of a fishing license, and subsequently to the expected benefits of a recreational fishing day. In contrast with previous studies, which have utilized travel cost or hypothetical market methods, our approach provides estimates that are directly comparable across geographic areas. Further, our results suggest that the benefits of recreational fishing days are generally less than previously estimated.
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- Peter A. Diamond & Jerry A. Hausman, 1994. "Contingent Valuation: Is Some Number Better than No Number?," Journal of Economic Perspectives, American Economic Association, vol. 8(4), pages 45-64, Fall.
- Carson, Richard T. & Flores, Nicholas E. & Martin, Kerry M. & Wright, Jennifer L., 1995.
"Contingent Valuation and Revealed Preference Methodologies: Comparing the Estimates for Quasi-Public Goods,"
1995 Conference (39th), February 14-16, 1995, Perth, Australia
148793, Australian Agricultural and Resource Economics Society.
- Richard T. Carson & Nicholas E. Flores & Kerry M. Martin & Jennifer L. Wright, 1996. "Contingent Valuation and Revealed Preference Methodologies: Comparing the Estimates for Quasi-Public Goods," Land Economics, University of Wisconsin Press, vol. 72(1), pages 80-99.
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