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

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• 作者：Trevor Collier ; Andrew L. Johnson ; John Ruggiero
• 关键词：DEA ; Stochastic frontier analysis ; Joint production
• 刊名：European Journal of Operational Research
• 出版年：2011
• 出版时间：16 January 2011
• 年：2011
• 卷：208
• 期：2
• 页码：153-160
• 全文大小：257 K

文摘

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.