Estimating Heterogeneous Production in Fisheries

Stochastic production frontier models are used extensively in the agricultural and resource economics literature to estimate production functions and technical efficiency, as well as to guide policy. Traditionally these models assume that each agent’s production can be specified as a representative,...

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Main Authors: Schnier, Kurt E., Anderson, Christopher M., Horrace, William C
Format: Text
Language:unknown
Published: SURFACE at Syracuse University 2006
Subjects:
tbd
Online Access:https://surface.syr.edu/ecn/133
https://surface.syr.edu/cgi/viewcontent.cgi?article=1028&context=ecn
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spelling ftsyracuseuniv:oai:surface.syr.edu:ecn-1028 2023-05-15T17:41:17+02:00 Estimating Heterogeneous Production in Fisheries Schnier, Kurt E. Anderson, Christopher M. Horrace, William C 2006-03-01T08:00:00Z application/pdf https://surface.syr.edu/ecn/133 https://surface.syr.edu/cgi/viewcontent.cgi?article=1028&context=ecn unknown SURFACE at Syracuse University https://surface.syr.edu/ecn/133 https://surface.syr.edu/cgi/viewcontent.cgi?article=1028&context=ecn Economics - Faculty Scholarship tbd Economics text 2006 ftsyracuseuniv 2022-01-09T19:20:51Z Stochastic production frontier models are used extensively in the agricultural and resource economics literature to estimate production functions and technical efficiency, as well as to guide policy. Traditionally these models assume that each agent’s production can be specified as a representative, homogeneous function. This paper proposes the synthesis of a latent class regression and an agricultural production frontier model to estimate technical efficiency while allowing for the possibility of production heterogeneity. We use this model to estimate a latent class production function and efficiency measures for vessels in the Northeast Atlantic herring fishery. Our results suggest that traditional measures of technical efficiency may be incorrect, if heterogeneity of agricultural production exists. Text Northeast Atlantic Syracuse University Research Facility And Collaborative Environment (SUrface)
institution Open Polar
collection Syracuse University Research Facility And Collaborative Environment (SUrface)
op_collection_id ftsyracuseuniv
language unknown
topic tbd
Economics
spellingShingle tbd
Economics
Schnier, Kurt E.
Anderson, Christopher M.
Horrace, William C
Estimating Heterogeneous Production in Fisheries
topic_facet tbd
Economics
description Stochastic production frontier models are used extensively in the agricultural and resource economics literature to estimate production functions and technical efficiency, as well as to guide policy. Traditionally these models assume that each agent’s production can be specified as a representative, homogeneous function. This paper proposes the synthesis of a latent class regression and an agricultural production frontier model to estimate technical efficiency while allowing for the possibility of production heterogeneity. We use this model to estimate a latent class production function and efficiency measures for vessels in the Northeast Atlantic herring fishery. Our results suggest that traditional measures of technical efficiency may be incorrect, if heterogeneity of agricultural production exists.
format Text
author Schnier, Kurt E.
Anderson, Christopher M.
Horrace, William C
author_facet Schnier, Kurt E.
Anderson, Christopher M.
Horrace, William C
author_sort Schnier, Kurt E.
title Estimating Heterogeneous Production in Fisheries
title_short Estimating Heterogeneous Production in Fisheries
title_full Estimating Heterogeneous Production in Fisheries
title_fullStr Estimating Heterogeneous Production in Fisheries
title_full_unstemmed Estimating Heterogeneous Production in Fisheries
title_sort estimating heterogeneous production in fisheries
publisher SURFACE at Syracuse University
publishDate 2006
url https://surface.syr.edu/ecn/133
https://surface.syr.edu/cgi/viewcontent.cgi?article=1028&context=ecn
genre Northeast Atlantic
genre_facet Northeast Atlantic
op_source Economics - Faculty Scholarship
op_relation https://surface.syr.edu/ecn/133
https://surface.syr.edu/cgi/viewcontent.cgi?article=1028&context=ecn
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