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Estimation of a Generalized Fishery Model: A Two-Stage Approach

Author

Listed:
  • Junjie Zhang

    (University of California, San Diego)

  • Martin D. Smith

    (Duke University)

Abstract

U.S. federal law calls for an end to overfishing, but measuring overfishing requires knowledge of bioeconomic parameters. Using microlevel economic data from the commercial fishery, this paper proposes a two-stage approach to estimate these parameters for a generalized fishery model. In the first stage, a fishery production function is consistently estimated by a within-period estimator treating the latent stock as a fixed effect. The estimated stock is then substituted into an equation of fish stock dynamics to estimate all other biological parameters. The bootstrap approach is used to correct the standard errors in the two-stage model. This method is applied to the reef-fish fishery in the northeastern Gulf of Mexico. The traditional method, which uses catch-per-unit-effort as a stock proxy, significantly overstates the optimal harvest level. © 2011 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Junjie Zhang & Martin D. Smith, 2011. "Estimation of a Generalized Fishery Model: A Two-Stage Approach," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 690-699, May.
  • Handle: RePEc:tpr:restat:v:93:y:2011:i:2:p:690-699
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    Cited by:

    1. Jonathan R. Sweeney & Richard E. Howitt & Hing Ling Chan & Minling Pan & PingSun Leung, 2017. "How do fishery policies affect Hawaii's longline fishing industry? Calibrating a positive mathematical programming model," Papers 1707.03960, arXiv.org.
    2. Sturla Kvamsdal & Diwakar Poudel & Leif Sandal, 2016. "Harvesting in a Fishery with Stochastic Growth and a Mean-Reverting Price," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 63(3), pages 643-663, March.
    3. repec:wsi:wepxxx:v:03:y:2017:i:02:n:s2382624x16500089 is not listed on IDEAS
    4. Burns, Christopher, 2014. "Measurement Error in the Schaefer Production Model," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170569, Agricultural and Applied Economics Association.

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