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

Research output: Contribution to journalArticle

11 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)729-745
Number of pages17
JournalJournal of Applied Econometrics
Volume22
Issue number4
DOIs
StatePublished - Jun 2007

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Economics and Econometrics

Fingerprint Dive into the research topics of 'Identifying technically efficient fishing vessels: A non-empty, minimal subset approach'. Together they form a unique fingerprint.

  • Cite this