Journal of Regulatory Economics

, Volume 28, Issue 2, pp 157–179 | Cite as

Using Revealed Preferences to Infer Environmental Benefits:Evidence from Recreational Fishing Licenses

  • Lori S. Bennear
  • Robert N. StavinsEmail author
  • Alexander F. Wagner


We develop and apply a new method for estimating the economic benefits of an environmental amenity. The method is based upon the notion of estimating the derived demand for a privately traded option to utilize an open access 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 15-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. Our findings show substantial variation in the value of a recreational fishing day across geographic areas in the United States. This suggests that current practice of using benefits estimates from one part of the country in national or regional analyses may lead to substantial bias in benefits estimates.


revealed-preference valuation environmental benefits recreational fishing day 

JEL Classification

Q26 Q21 Q22 H41 


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Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • Lori S. Bennear
    • 1
  • Robert N. Stavins
    • 2
    Email author
  • Alexander F. Wagner
    • 3
  1. 1.Nicholas School of the Environment and Earth SciencesDuke UniversityDurhamUSA
  2. 2.John F. Kennedy School of GovernmentHarvard University and Resources for the FutureCambridgeUSA
  3. 3.Swiss Banking InstituteUniversity of ZurichZurichSwitzerland

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