短期约翰森基于边界的产业模型:渔业的方法改进和实证说明

IF 2.3 4区 经济学 Q3 BUSINESS
Kristiaan Kerstens, Jafar Sadeghi, Ignace Van De Woestyne, John Walden
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引用次数: 0

摘要

这篇文章着重从三个方面扩展了以短期约翰森工业模型为名的中央资源分配计划模型的现状。首先,我们纠正了一个长期存在的问题,即正确选择产能分布的权重变量,保证这些权重决定了生产组合,这些生产组合属于工厂产能估计首先基于的生产技术。其次,我们利用平均实践和最佳实践模型之间的差距,通过引入效率改进命令,在计划时允许部分技术效率低下。第三,我们不是只考虑以产量为导向的工厂产能,而是考虑其他工厂产能概念。特别是,我们引入了一个以投入为导向的工厂产能概念,以及一个可替代的以产出为导向的工厂产能概念,该概念纠正了传统的以产出为导向的工厂产能概念中的一个主要经验问题。通过开发一个规划模型来遏制过度捕捞,这些方法的改进用美国渔船的数据集来说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Short-run Johansen frontier-based industry models: methodological refinements and empirical illustration on fisheries

Short-run Johansen frontier-based industry models: methodological refinements and empirical illustration on fisheries
This contribution focuses on extending the current state of the art in a central resource allocation planning model known under the name of the short-run Johansen industry model in three ways. First, we correct a long-standing issue of the correct choice of weight variables on the capacity distribution by guaranteeing that these weights determine production combinations that belong to the production technology on which the plant capacity estimates are based in the first place. Second, we exploit the gap between average practice and best practice models by introducing an efficiency improvement imperative that allows for partial technical inefficiency when planning. Third, instead of only considering output-oriented plant capacity, we allow for alternative plant capacity concepts. In particular, we introduce an input-oriented plant capacity concept, and an alternative attainable output-oriented plant capacity concept that corrects a major empirical issue in the traditional output-oriented plant capacity notion. These methodological refinements are illustrated with a data set on U.S. fishing vessels by developing a planning model to curb overfishing.
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来源期刊
CiteScore
3.10
自引率
6.20%
发文量
30
期刊介绍: The Journal of Productivity Analysis publishes theoretical and applied research that addresses issues involving the measurement, explanation, and improvement of productivity. The broad scope of the journal encompasses productivity-related developments spanning the disciplines of economics, the management sciences, operations research, and business and public administration. Topics covered in the journal include, but are not limited to, productivity theory, organizational design, index number theory, and related foundations of productivity analysis. The journal also publishes research on computational methods that are employed in productivity analysis, including econometric and mathematical programming techniques, and empirical research based on data at all levels of aggregation, ranging from aggregate macroeconomic data to disaggregate microeconomic data. The empirical research illustrates the application of theory and techniques to the measurement of productivity, and develops implications for the design of managerial strategies and public policy to enhance productivity. Officially cited as: J Prod Anal
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