Journal article

Estimation and efficiency measurement in stochastic production frontiers with ordinal outcomes

William Griffiths, Xiaohui Zhang, Xueyan Zhao

Journal of Productivity Analysis | SPRINGER | Published : 2014

Abstract

We consider Bayesian estimation of a stochastic production frontier with ordered categorical output, where the inefficiency error is assumed to follow an exponential distribution, and where output, conditional on the inefficiency error, is modelled as an ordered probit model. Gibbs sampling algorithms are provided for estimation with both cross-sectional and panel data, with panel data being our main focus. A Monte Carlo study and a comparison of results from an example where data are used in both continuous and categorical form supports the usefulness of the approach. New efficiency measures are suggested to overcome a lack-of-invariance problem suffered by traditional efficiency measures. ..

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University of Melbourne Researchers