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

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