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Technical Efficiency of the Danish Trawl fleet: Are the Industrial Vessels Better than Others?

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Author Info

  • Niels Vestergaard

    ()
    (Department of Environmental and Business Economics, University of Southern Denmark)

  • Dale Squires

    ()
    (U.S. National Institute of Marine Science, Southwest Fisheries Science Center)

  • Frank Jensen

    ()
    (Institute of Local Government Studies, Denmark)

  • Jesper L. Andersen

    ()
    (Danish Research Institute of Food Economics, Fisheries Economics and Management Division)

Abstract

Technical efficiency in the Danish trawl fishery in the North Sea is estimated for 1997 and 1998 by a stochastic production frontier model. This model allows noise when the frontier and the technical efficiency is found, which for fisheries is a reasonable assumption. The results show that the production frontier can be modelled by a translog function without time effects and a technical ineffi-ciency function. The type of fishery (industrial or consumption), size of vessel (greater or lesser than 60 GRT) and year give a good explanation for the ineffi-ciency in the fleet. The average technical efficiency is estimated to be 0.82. On average, industrial vessels have a higher technical efficiency than human con-sumption vessels, and smaller vessels have higher technical efficiency than lar-ger vessels. In sum, the analysis reveals that vessel larger than 60 GRT and fishing industrial species are the most efficient.

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Bibliographic Info

Paper provided by University of Southern Denmark, Department of Environmental and Business Economics in its series Working Papers with number 32/02.

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Length: 30 pages
Date of creation: Jun 2002
Date of revision:
Handle: RePEc:sdk:wpaper:32

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Related research

Keywords: Technical efficiency; stochastic production frontier; Danish trawl fishery;

References

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  1. Campbell, H. F. & Hand, A. J., 1998. "Joint ventures and technology transfer: the Solomon Islands pole-and-line fishery," Journal of Development Economics, Elsevier, vol. 57(2), pages 421-442.
  2. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
  3. Eggert, Håkan, 2001. "Technical efficiency in the Swedish trawl fishery for Norway lobster," Working Papers in Economics 53, University of Gothenburg, Department of Economics.
  4. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-86, July.
  5. Kumbhakar, Subal C., 1987. "The specification of technical and allocative inefficiency in stochastic production and profit frontiers," Journal of Econometrics, Elsevier, vol. 34(3), pages 335-348, March.
  6. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
  7. Kodde, David A & Palm, Franz C, 1986. "Wald Criteria for Jointly Testing Equality and Inequality Restriction s," Econometrica, Econometric Society, vol. 54(5), pages 1243-48, September.
  8. Grafton, R.Q. & Squires, D. & Fox, K.J., 1998. "Private Property and Economic Efficiency: A Study of a Common-Pool Resource," Working Papers 9804e, University of Ottawa, Department of Economics.
  9. Fare, Rolf & Grosskopf, Shawna & Kokkelenberg, Edward C, 1989. "Measuring Plant Capacity, Utilization and Technical Change: A Nonparametric Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 655-66, August.
  10. 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.
  11. 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.
  12. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-44, June.
  13. Kim, H Youn, 1992. "The Translog Production Function and Variable Returns to Scale," The Review of Economics and Statistics, MIT Press, vol. 74(3), pages 546-52, August.
  14. Reifschneider, David & Stevenson, Rodney, 1991. "Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(3), pages 715-23, August.
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Citations

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Cited by:
  1. Birgit Nahrstedt & Henning P. Jørgensen & Ayoe Hoff, 2002. "Estimation of Production Functions on Fishery: A Danish Survey," Working Papers 33/02, University of Southern Denmark, Department of Environmental and Business Economics.
  2. Nazneen K. Chowdhury & Tom Kompas & Kaliappa Kalirajan, 2010. "Impact of control measures in fisheries management: evidence from Bangladesh's industrial trawl fishery," Economics Bulletin, AccessEcon, vol. 30(1), pages 765-773.

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