Ordinal principal component analysis for a common ranking of stochastic frontiers

Scippacercola Sergio; Sepe Enrica

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Ordinal principal component analysis for a common ranking of stochastic frontiers

机译：随机前沿共同排序的序数主成分分析

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The Stochastic Frontier Analysis (SFA) is a model to evaluate the Technical Efficiency (TE) for Production Units (PU). When SFA is applied on different output variables with same input, the analysis estimates different TEs for the PU. We refer to these TEs as the Multiple Technical Efficiency (MTE) of the PU. In this work, we present a method to unify the MTE in one ranking, in order to compute a synthetic index of the TE based on a parametric model. Our approach transforms the measures of efficiency into values on an ordinal scale. Then, using the Ordinal Principal Component Analysis and a genetic algorithm, we merge the multiple rankings.

机译：随机前沿分析（SFA）是评估生产单位（PU）的技术效率（TE）的模型。当SFA应用于具有相同输入的不同输出变量时，分析会估计PU的不同TE。我们将这些TE称为PU的多重技术效率（MTE）。在这项工作中，我们提出了一种统一MTE的方法，以便基于参数模型计算TE的综合指数。我们的方法将效率的度量转换为有序规模的值。然后，使用有序主成分分析和遗传算法，我们合并了多个排名。

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《Journal of applied statistics》 |2016年第16期|2442-2451|共10页
作者
Scippacercola Sergio; Sepe Enrica;
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作者单位

Univ Naples Federico II, Dept Econ, Inst, Management, Via Cinthia, I-80126 Naples, Italy;

Univ Naples Federico II, Dept Econ, Inst, Management, Via Cinthia, I-80126 Naples, Italy;

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正文语种 eng
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关键词
Technical efficiency; multiple technical efficiency; ordinal scale; production unit; ranking;

机译：技术效率;多项技术效率;常规规模;生产单位;排名;

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Ordinal principal component analysis for a common ranking of stochastic frontiers

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