Estimating Heterogeneous Production in Fisheries

Kurt Schnier (), Christopher M. Anderson and William Horrace
Additional contact information
Christopher M. Anderson: Department of Environmental and Natural Resource Economics, University of Rhode Island

No 80, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

Abstract: 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 aagricultural 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.

Keywords: latent class regression; EC algorithm; stochastic production frontier; technical efficiency (search for similar items in EconPapers)
JEL-codes: D24 N52 (search for similar items in EconPapers)
Pages: 39 pages
Date: 2006-03
New Economics Papers: this item is included in nep-agr, nep-ecm and nep-eff
References: Add references at CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://surface.syr.edu/cpr/84/ (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:max:cprwps:80

Access Statistics for this paper

More papers in Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University 426 Eggers Hall, Syracuse, New York USA 13244-1020. Contact information at EDIRC.
Bibliographic data for series maintained by Katrina Fiacchi ().