Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach
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 assumpti...
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ftsyracuseuniv:oai:surface.syr.edu:ecn-1031 2023-05-15T17:41:24+02:00 Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach Horrace, William C Schnier, Kurt E. Flores-Lagunes, Alfonso 2006-03-01T08:00:00Z application/pdf https://surface.syr.edu/ecn/130 https://surface.syr.edu/cgi/viewcontent.cgi?article=1031&context=ecn unknown SURFACE at Syracuse University https://surface.syr.edu/ecn/130 https://surface.syr.edu/cgi/viewcontent.cgi?article=1031&context=ecn Economics - Faculty Scholarship tbd Economics text 2006 ftsyracuseuniv 2022-01-09T19:20:51Z 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 homogenous and heterogeneous production functions within the fleet. When homogenous 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. Text Northeast Atlantic Syracuse University Research Facility And Collaborative Environment (SUrface) |
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Syracuse University Research Facility And Collaborative Environment (SUrface) |
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tbd Economics |
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tbd Economics Horrace, William C Schnier, Kurt E. Flores-Lagunes, Alfonso Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach |
topic_facet |
tbd Economics |
description |
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 homogenous and heterogeneous production functions within the fleet. When homogenous 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. |
format |
Text |
author |
Horrace, William C Schnier, Kurt E. Flores-Lagunes, Alfonso |
author_facet |
Horrace, William C Schnier, Kurt E. Flores-Lagunes, Alfonso |
author_sort |
Horrace, William C |
title |
Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach |
title_short |
Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach |
title_full |
Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach |
title_fullStr |
Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach |
title_full_unstemmed |
Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach |
title_sort |
identifying technically efficient fishing vessels: a non-empty, minimal subset approach |
publisher |
SURFACE at Syracuse University |
publishDate |
2006 |
url |
https://surface.syr.edu/ecn/130 https://surface.syr.edu/cgi/viewcontent.cgi?article=1031&context=ecn |
genre |
Northeast Atlantic |
genre_facet |
Northeast Atlantic |
op_source |
Economics - Faculty Scholarship |
op_relation |
https://surface.syr.edu/ecn/130 https://surface.syr.edu/cgi/viewcontent.cgi?article=1031&context=ecn |
_version_ |
1766142944560021504 |