Title

Technical Efficiency Estimation with Multiple Inputs and Multiple Outputs Using Regression Analysis

Document Type

Article

Publication Date

1-2011

Publication Source

European Journal of Operational Research

Abstract

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.

Inclusive pages

153-160

ISBN/ISSN

0377-2217

Publisher

Elsevier

Volume

208

Issue

2

Peer Reviewed

yes