Microfoundations for stochastic frontiers

Tsionas, Efthymios (2017) Microfoundations for stochastic frontiers. European Journal of Operational Research, 258 (3). pp. 1165-1170. ISSN 0377-2217

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The purpose of the paper is to propose microfoundations for stochastic frontier models. Previous work shows that a simple Bayesian learning model supports gamma distributions for technical inefficiency in stochastic frontier models. The conclusion depends on how the problem is formulated and what assumptions are made about the sampling process and the prior. After the new formulation of the problem it turns out that the distribution of the one-sided error component does not belong to a known family. Moreover, we find that without specifying a utility function or even the cost inefficiency function, the relative effectiveness of managerial input can be determined using only cost data and estimates of the returns to scale. The point of this construction is that features of the inefficiency function u(z) can be recovered from the data, based on the solid microfoundation of expected utility of profit maximization but the model does not make a prediction about the distribution.

Item Type:
Journal Article
Journal or Publication Title:
European Journal of Operational Research
Additional Information:
This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. 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 European Journal of Operational Research, 258, 3, 2017 DOI: 10.1016/j.ejor.2016.09.033
Uncontrolled Keywords:
?? economicsstochastic frontier analysismicrofoundationsbayesian learninglearning-by-doingmodelling and simulationmanagement science and operations researchinformation systems and management ??
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Deposited On:
27 Sep 2016 15:40
Last Modified:
20 Feb 2024 00:43