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Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach

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Abstract

There is a growing resource economics literature, concerning the estimation of the technical efficiency of fishing vessels utilizing the stochastic frontier model. In these models, vessel output is regressed on a linear function of vessel inputs and a random composed error. Using parametric assumptions on the regression residual, estimates of vessel technical efficiency are calculated as the mean of a truncated normal distribution and are often reported in a rank statistic as a measure of a captain's skill and used to estimate excess capacity within fisheries. We demonstrate analytically that these measures are potentially flawed, and extend the results of Horrace (2005) to estimate captain skill for thirty-nine vessels in the Northeast Atlantic herring fleet, based on homogeneous and heterogeneous production functions within the fleet. When homogeneous production is assumed, we find inferential inconsistencies between our methods and the methods of ranking the means of the technical inefficiency distributions for each vessel. When production is allowed to be heterogeneous, these inconsistencies are mitigated.

Suggested Citation

  • Alfonso Flores-Lagunes & William C. Horrace & Kurt E. Schnier, 2006. "Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach," Center for Policy Research Working Papers 78, Center for Policy Research, Maxwell School, Syracuse University.
  • Handle: RePEc:max:cprwps:78
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    1. El-Gamal, Mahmoud A. & Grether, David M., 1995. "Are People Bayesian? Uncovering Behavioral Strategies," Working Papers 919, California Institute of Technology, Division of the Humanities and Social Sciences.
    2. Fernandez C. & Koop G. & Steel M.F.J., 2002. "Multiple-Output Production With Undesirable Outputs: An Application to Nitrogen Surplus in Agriculture," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 432-442, June.
    3. Kurt E. Schnier & Christopher M. Anderson & William C. Horrace, 2006. "Estimating Heterogeneous Production in Fisheries," Center for Policy Research Working Papers 80, Center for Policy Research, Maxwell School, Syracuse University.
    4. Sean Pascoe & Louisa Coglan, 2002. "The Contribution of Unmeasurable Inputs to Fisheries Production: An Analysis of Technical Efficiency of Fishing Vessels in the English Channel," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(3), pages 585-597.
    5. William Horrace & Joseph Marchand & Timothy Smeeding, 2008. "Ranking inequality: Applications of multivariate subset selection," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(1), pages 5-32, March.
    6. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, University Library of Munich, Germany.
    7. Scott Atkinson & Jeffrey Dorfman, 2005. "Multiple Comparisons with the Best: Bayesian Precision Measures of Efficiency Rankings," Journal of Productivity Analysis, Springer, vol. 23(3), pages 359-382, July.
    8. 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.
    9. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    10. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    11. 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.
    12. Horrace, William C., 2005. "On ranking and selection from independent truncated normal distributions," Journal of Econometrics, Elsevier, vol. 126(2), pages 335-354, June.
    13. 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.
    14. 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.
    15. William C. Horrace & Peter Schmidt, 2000. "Multiple comparisons with the best, with economic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 1-26.
    16. Trond Bjørndal, 1989. "Production in a Schooling Fishery: The Case of the North Sea Herring Fishery," Land Economics, University of Wisconsin Press, vol. 65(1), pages 49-56.
    17. James Kirkley & Catherine Morrison Paul & Dale Squires, 2002. "Capacity and Capacity Utilization in Common-pool Resource Industries," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 22(1), pages 71-97, June.
    18. Battese, George E. & Coelli, Tim J. & Colby, T.C., 1989. "Estimation of Frontier Production Functions and the Efficiencies of Indian Farms Using Panel Data from ICRISAT's Village Level Studies," 1989 Conference (33rd), February 7-9, 1989, Christchurch, New Zealand 144383, Australian Agricultural and Resource Economics Society.
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    Cited by:

    1. William Horrace & Christopher Parmeter, 2016. "Accounting for Multiplicity in Inference on Economics Journal Rankings," Working Papers 2016-08, University of Miami, Department of Economics.
    2. William Horrace & Seth Richards-Shubik & Ian Wright, 2015. "Expected efficiency ranks from parametric stochastic frontier models," Empirical Economics, Springer, vol. 48(2), pages 829-848, March.
    3. Ronald Felthoven & William Horrace & Kurt Schnier, 2009. "Estimating heterogeneous capacity and capacity utilization in a multi-species fishery," Journal of Productivity Analysis, Springer, vol. 32(3), pages 173-189, December.
    4. Abbott, Joshua K. & Wilen, James E., 2009. "Regulation of fisheries bycatch with common-pool output quotas," Journal of Environmental Economics and Management, Elsevier, vol. 57(2), pages 195-204, March.
    5. Phill Wheat & William Greene & Andrew Smith, 2014. "Understanding prediction intervals for firm specific inefficiency scores from parametric stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 55-65, August.
    6. repec:taf:emetrv:v:37:y:2018:i:3:p:260-280 is not listed on IDEAS
    7. William C. Horrace & Christopher F. Parmeter, 2018. "A Laplace stochastic frontier model," Econometric Reviews, Taylor & Francis Journals, vol. 37(3), pages 260-280, March.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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    1. Socio-economics of Fisheries and Aquaculture

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