Identifying technically efficient fishing vessels: a non-empty, minimal subset approach

Alfonso Flores-Lagunes (), William C. Horrace () and Kurt E. Schnier
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Kurt E. Schnier: Department of Environmental and Natural Resource Economics, University of Rhode Island, Kingston, Rhode Island, USA, Postal: Department of Environmental and Natural Resource Economics, University of Rhode Island, Kingston, Rhode Island, USA

Journal of Applied Econometrics, 2007, vol. 22, issue 4, pages 729-745

Abstract: Stochastic frontier models are often employed to estimate fishing vessel technical efficiency. Under certain assumptions, these models yield efficiency measures that are means of truncated normal distributions. We argue that these measures are flawed, and use the results of Horrace (2005) to estimate efficiency for 39 vessels in the Northeast Atlantic herring fleet, based on each vessel's probability of being efficient. We develop a subset selection technique to identify groups of efficient vessels at pre-specified probability levels. When homogeneous production is assumed, inferential inconsistencies exist 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. Copyright © 2007 John Wiley & Sons, Ltd.

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Related works:
Working Paper: Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach (2006)
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