Journal Article

A new approach to estimating the metafrontier production function based on a stochastic frontier framework

Huang, Tai-Hsin, Huang, Cliff J., Liu, Nan-Hung

2014

Overview

This paper proposes a new two-step stochastic frontier approach to estimate technical efficiency (TE) scores for firms in different groups adopting distinct technologies. Analogous to Battese et al. (J Prod Anal 21:91-103, 2004), the metafrontier production function allows for calculating comparable TE measures, which can be decomposed into group specific TE measures and technology gap ratios. The proposed approach differs from Battese et al. (J Prod Anal 21:91-103, 2004) and O'Donnell et al. (Empir Econ 34:231-255, 2008) mainly in the second step, where a stochastic frontier analysis model is formulated and applied to obtain the estimates of the metafrontier, instead of relying on programming techniques. The so-derived estimators have the desirable statistical properties and enable the statistical inferences to be drawn. While the within-group variation in firms' technical efficiencies is frequently assumed to be associated with firm-specific exogenous variables, the between-group variation in technology gaps can be specified as a function of some exogenous variables to take account of group-specific environmental differences. Two empirical applications are illustrated and the results appear to support the use of our model.

• Publisher: Spring Science+Business Media,Springer US,Springer Nature B.V
• Subject: Accounting/Auditing / Econometrics / Economic models / Economics / Economics and Finance / Efficiency / Efficiency metrics / Environmental technology / Estimation methods / Hotel industry / Mathematical functions / Maximum likelihood estimation / Microeconomics / Operations Research/Decision Theory / Production estimates / Production functions / Standard error / Stochastic models