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Determining policy-efficient management strategies in fisheries using data envelopment analysis (DEA)

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  • Griffin, Wade L.
  • Woodward, Richard T.

Abstract

In this paper, the authors analyze a wide range of recreational management strategies for their impacts on red snapper yield, economic surplus and the fish stock. Simulating a wide range of policies, the authors find Data Envelopment Analysis (DEA) inspired policy efficiency frontiers that lead to finding those management strategies that offer the greatest level of economic surplus for any biological target, looking at both the east and west Gulf of Mexico fisheries. Red snapper has been declared overfished since 1988 and the 2005 SEDAR 7 stock assessment declared red snapper were overfished and undergoing overfishing. In November 2009, the update of the assessment declared that overfishing was no longer occurring but that the red snapper stocks needed to be rebuilt. In this analysis, it was found that red snapper are neither overfished or undergoing overfishing. The main difference between the present model and the SEDAR 7 model is that the latest model uses a higher mortality rate for juveniles and a density dependent model. The authors also suggest that the east and west should be managed as separate units.

Suggested Citation

  • Griffin, Wade L. & Woodward, Richard T., 2011. "Determining policy-efficient management strategies in fisheries using data envelopment analysis (DEA)," Marine Policy, Elsevier, vol. 35(4), pages 496-507, July.
    • Handle: RePEc:eee:marpol:v:35:y:2011:i:4:p:496-507
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    Cited by:

    1. Pascoe, Sean & Hutton, Trevor & Hoshino, Eriko & Sporci, Miriana & Yamasaki, Satoshi & Kompas, Tom, 2020. "Effectiveness of harvest strategies in achieving multiple management objectives in a multispecies fishery," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(3), July.
    2. Song Wang & Caizhi Sun & Xin Li & Wei Zou, 2016. "Sustainable Development in China’s Coastal Area: Based on the Driver-Pressure-State-Welfare-Response Framework and the Data Envelopment Analysis Model," Sustainability, MDPI, vol. 8(9), pages 1-19, September.
    3. Osvaldo U. Becerril-Torres & Gabriela Rodríguez Licea & Javier Jesús Ramírez Hernández, 2011. "Technical efficiency of the agricultural sector in Mexico: An overview of data envelopment analysis," Economía, Instituto de Investigaciones Económicas y Sociales (IIES). Facultad de Ciencias Económicas y Sociales. Universidad de Los Andes. Mérida, Venezuela, vol. 36(31), pages 85-110, January-j.
    4. Dowling, Natalie A. & Dichmont, Catherine M. & Leigh, George M. & Pascoe, Sean & Pears, Rachel J. & Roberts, Tom & Breen, Sian & Cannard, Toni & Mamula, Aaron & Mangel, Marc, 2020. "Optimising harvest strategies over multiple objectives and stakeholder preferences," Ecological Modelling, Elsevier, vol. 435(C).

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