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Technical efficiency estimation with multiple inputs and multiple outputs using regression analysis

delete2011-01-01
delete31
PRE
AI
T
Trevor Collier
A
Andrew L. Johnson
J
John Ruggiero *
DOI:10.1016/j.ejor.2010.08.024delete
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摘要

摘要

En 中文
Regression and linear programming provide the basis for popular techniques for estimating technical efficiency Regression-based approaches are typically parametric and can be both deterministic or stochastic where the later allows for measurement error In contrast linear programming models are nonparametric and allow multiple Inputs and outputs The purported disadvantage of the regression-based models is the inability to allow multiple outputs without additional data on input prices In this paper deterministic cross-sectional and stochastic panel data regression models that allow multiple inputs and outputs are developed Notably technical efficiency can be estimated using regression models characterized by multiple input multiple output environments without Input price data We provide multiple examples including a Monte Carlo analysis (C) 2010 Elsevier B V All rights reserved
Keyword:
DEA
Stochastic frontier analysis
Joint production
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期刊

European Journal of Operational Research 封面图
European Journal of Operational Research
IF:
6
论文数:
2.2W
被引数:
6.4W

机构

U
University System of Ohio
学者数:
15.5W
论文数: 13.0W
被引数: 200
U
University of Dayton
学者数:
1.3K
论文数: 1.1K
被引数: 1.8K
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