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Catch, Efficiency and Management: A Stochastic Production Frontier Analysis of the Australian Northern Prawn Fishery


  • Tom Kompas


This paper is a study of the production technology and relative efficiency of vessels harvesting banana and tiger prawns in the Northern Prawn Fishery (NPF), one of Australia’s largest and most lucrative fishing areas. It is based on an unbalanaced panel data set of 226 observations among thirty-seven vessels for the years 1990-1996 and employs a technique which specifies a stochastic frontier production function in order to decompose the variation among vessels in the harvest of prawns due to unbounded random effects beyond firm control from those that result in differences in technical inefficiency among fishing vessels in the industry. In other words, variations in maximum expected output can occure either as a result of stochastic effects (e.g., good and bad weather states), or from the fact that vessels in the industry may be operating at various levels of inefficiency due to mismanagement, poor incentive structures, less than perfectly competitive behaviour or inappropriate input levels or combinations. Estimation of this output frontier also provides key information on the relative importance of inputs in the production of banana and tiger prawns, output elasticities, returns to scale, possible variations in stock size and the economic performance of each fishing vessel, year to year. Likelihood ratio tests confirm that both stochastic effects and the extent of technical inefficiency matter, thus making traditional OLS estimates inappropriate. The level of technical inefficiency is shown to depend positively on gear headrope length and negatively on either the number of A-units or fuel expenditures. The point is especially relevant since A-unit restrictions over vessel size and engine power in the fishery during this period appear to have resulted in a substitution toward less efficient but unregulated inputs, such as gear headrope length. In this regard, the recent introduction of gear headrope length restrictions may be justified on two counts, both as a device to limit effor or tach and protect prawn stocks and as a way, given the final estimates in this paper, of improving economic performance by increasing the technical efficiency of vessels remaining in the industry. Nevertheless, it is important to emphasize that restrictions on an existing inefficient input may result in far smaller reductions in effort than projected, since the technical efficiency of vessels in the fishery will rise. With an increase in technical efficiency, gear-restricted fishing firms will harvest at points closer to their output frontiers. Moreover, with the removal of A-unit restrictions, ‘effort creep’ in the form of larger vessels and more powerful engines may more than compensate for any decrease in effort due to gear reduction.

Suggested Citation

  • Tom Kompas, 2001. "Catch, Efficiency and Management: A Stochastic Production Frontier Analysis of the Australian Northern Prawn Fishery," International and Development Economics Working Papers idec01-8, International and Development Economics.
  • Handle: RePEc:idc:wpaper:idec01-8

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    References listed on IDEAS

    1. D. S. Prasada Rao & Bart van Ark, 2013. "Introduction," Chapters,in: World Economic Performance, chapter 1, pages 1-6 Edward Elgar Publishing.
    2. Coelli, Tim J. & Battese, George E., 1996. "Identification Of Factors Which Influence The Technical Inefficiency Of Indian Farmers," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 40(02), August.
    3. Schmidt, Peter & Knox Lovell, C. A., 1979. "Estimating technical and allocative inefficiency relative to stochastic production and cost frontiers," Journal of Econometrics, Elsevier, vol. 9(3), pages 343-366, February.
    4. 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 435-444, June.
    5. Forsund, Finn R. & Lovell, C. A. Knox & Schmidt, Peter, 1980. "A survey of frontier production functions and of their relationship to efficiency measurement," Journal of Econometrics, Elsevier, vol. 13(1), pages 5-25, May.
    6. 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.
    7. 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 279-286, July.
    8. Kodde, David A & Palm, Franz C, 1986. "Wald Criteria for Jointly Testing Equality and Inequality Restriction s," Econometrica, Econometric Society, vol. 54(5), pages 1243-1248, September.
    9. 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(03), December.
    10. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    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.
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    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q22 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Fishery

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