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

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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.

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Paper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 78.

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Length: 29 pages
Date of creation: Mar 2006
Date of revision:
Handle: RePEc:max:cprwps:78

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  1. Horrace, William C., 2005. "On ranking and selection from independent truncated normal distributions," Journal of Econometrics, Elsevier, vol. 126(2), pages 335-354, June.
  2. KOOP , Gary & OSIEWALSKI , Jacek & STEEL , Mark, 1995. "Bayesian Efficiency Analysis through Individual Effects : Hospital Cost Frontiers," CORE Discussion Papers 1995036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  3. 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 325-32.
  4. 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.
  5. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA.
  6. 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.
  7. Carmen Fernandez & Gary Koop & Mark F J Steel, 2004. "Multiple-output production with undesirable output: An application to nitrogen surplus in agriculture," ESE Discussion Papers 34, Edinburgh School of Economics, University of Edinburgh.
  8. Tsionas, E.G., 2001. "Stochastic Frontier Models with Random Coefficients," Athens University of Economics and Business 130, Athens University of Economics and Business, Department of International and European Economic Studies.
  9. 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.
  10. 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.
  11. William C. Horrace & Joseph T. Marchand & Timothy M. Smeeding, 2006. "Ranking Inequality: Applications of Multivariate Subset Selection," Working Papers 21, ECINEQ, Society for the Study of Economic Inequality.
  12. 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.
  13. 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.
  14. 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.
  15. James Kirkley & Catherine Morrison Paul & Dale Squires, 2002. "Capacity and Capacity Utilization in Common-pool Resource Industries," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 22(1), pages 71-97, June.
  16. 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.
  17. 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.
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Cited by:
  1. Ronald G. Felthovan & William C. Horrace & Kurt E. Schnier, 2006. "Estimating Heterogeneous Capacity and Capacity Utilization in a Multi-Species Fishery," Center for Policy Research Working Papers 86, Center for Policy Research, Maxwell School, Syracuse University.
  2. William C. Horrace & Christopher F. Parmeter, 2014. "A Laplace Stochastic Frontier Model," Center for Policy Research Working Papers 166, Center for Policy Research, Maxwell School, Syracuse University.
  3. William Horrace & Seth Richards-Shubik, 2013. "Expected Efficiency Ranks From Parametric Stochastic Fronteir Models," Center for Policy Research Working Papers 153, Center for Policy Research, Maxwell School, Syracuse University.
  4. 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.

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  1. Socio-economics of Fisheries and Aquaculture

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