The profit function system with output- and input-specific technical efficiency

Tsionas, Mike G. (2017) The profit function system with output- and input-specific technical efficiency. Economics Letters, 151. pp. 111-114. ISSN 0165-1765

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Abstract

In a recent paper Kumbhakar and Lai (2016) proposed an output-oriented non-radial measure of technical inefficiency derived from the revenue function. They proposed a closed skew-normal distribution for maximum likelihood estimation but they did not apply the model to data and their technique depends on multiple evaluations of multivariate normal integrals for each observation which can be very costly. In this paper we extend their approach to the profit function and we propose both input- and output-oriented non-radial measures of technical inefficiencies. Although the extension to the translog profit function is trivial many observations, in practice, may contain negative profits. For this reason we provide a nontrivial extension to the Symmetric Generalized McFadden (SGM) profit function. We propose and apply (to a large sample of US banks) Bayesian analysis of the SGM model (augmented with latent technical inefficiencies resulting in a highly nonlinear mixed effects model) using the integrated nested Laplace approximation.

Item Type:
Journal Article
Journal or Publication Title:
Economics Letters
Additional Information:
This is the author’s version of a work that was accepted for publication in Economics Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Economics Letters, 151, 2017 DOI: 10.1016/j.econlet.2016.012.020
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2000/2002
Subjects:
ID Code:
83864
Deposited By:
Deposited On:
06 Jan 2017 16:42
Refereed?:
Yes
Published?:
Published
Last Modified:
27 Sep 2020 03:41