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Productive Efficiency of Connecticut Long Island Lobster Fishery Using a Finite Mixture Model

Author

Listed:
  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Zinnia Mukherjee

    (Department of Economics, Simmons College, 300 The Fenway, E-203J, Boston, MA 02115, USA)

  • Mike G. Tsionas

    (Lancaster University Management School, LA1 4YX U.K.; Athens University of Economics and Business, Greece)

  • Peter Wanke

    (COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal Lemme, 355. 21949-900 Rio de Janeiro)

Abstract

This paper evaluates the operational practices of three lobster fishing zones in Long Island using a finite mixture model that allows controlling for unobserved heterogeneity. More precisely, a stochastic frontier latent class model is adopted in this research to estimate the production frontiers for each of the different technologies embedded within this heterogeneity. Therefore, this model not only enables the identification of different groups within the fishing zones, but it also permits the analysis of their productive efficiency. Results indicate the existence of five different technology groups within the sample, suggesting that production technologies in lobster fishery are themselves quite heterogeneous despite the environmental conditions. Policy implications are also derived.

Suggested Citation

  • Rangan Gupta & Zinnia Mukherjee & Mike G. Tsionas & Peter Wanke, 2016. "Productive Efficiency of Connecticut Long Island Lobster Fishery Using a Finite Mixture Model," Working Papers 201614, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201614
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    References listed on IDEAS

    as
    1. Tom Kompas & Tuong Nhu Che & R. Quentin Grafton, 2004. "Technical efficiency effects of input controls: evidence from Australia's banana prawn fishery," Applied Economics, Taylor & Francis Journals, vol. 36(15), pages 1631-1641.
    2. Leisch, Friedrich, 2004. "FlexMix: A General Framework for Finite Mixture Models and Latent Class Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i08).
    3. William Greene, 2004. "Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization's panel data on national health care systems," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 959-980, October.
    4. Lei Chen & Rangan Gupta & Zinnia Mukherjee & Peter Wanke, 2016. "Technical efficiency of Connecticut Long Island Sound lobster fishery: a nonparametric approach to aggregate frontier analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(3), pages 1533-1548, April.
    5. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    6. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
    7. Ferdinand D. Vinuya, 2010. "Technical efficiency of shrimp fishery in South Carolina, USA," Applied Economics Letters, Taylor & Francis Journals, vol. 17(1), pages 1-5, January.
    8. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    9. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
    10. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 1-11, December.
    11. James E. Kirkley & Dale Squires & Ivar E. Strand, 1995. "Assessing Technical Efficiency in Commercial Fisheries: The Mid-Atlantic Sea Scallop Fishery," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(3), pages 686-697.
    12. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    14. Asche, Frank & Roll, Kristin H. & Tveteras, Ragnar, 2009. "Economic inefficiency and environmental impact: An application to aquaculture production," Journal of Environmental Economics and Management, Elsevier, vol. 58(1), pages 93-105, July.
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    More about this item

    Keywords

    Long Island Sound; lobster fishery; stochastic production frontier; latent class model; technical efficiency; panel data;
    All these keywords.

    JEL classification:

    • Q22 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Fishery
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics

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