Technical and allocative inefficiency in production systems: a vine copula approach

Zhai Jian (), James Robert () and Artem Prokhorov
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Zhai Jian: Discipline of Business Analytics, Business School, University of Sydney, Sydney, NSW, Australia
James Robert: Discipline of Business Analytics, Business School, University of Sydney, Sydney, NSW, Australia

Dependence Modeling, 2022, vol. 10, issue 1, 145-158

Abstract: Modeling the error terms in stochastic frontier models of production systems requires multivariate distributions with certain characteristics. We argue that canonical vine copulas offer a natural way to model the pairwise dependence between the two main error types that arise in production systems with multiple inputs. We introduce a vine copula construction that permits dependence between the magnitude (but not the sign) of the errors. By using a recently proposed family of copulas, we show how to construct a simulated likelihood based on C-vines. We discuss issues that arise in the estimation of such models and outline why such models better reflect the dependencies that arise in practice. Monte Carlo simulations and a classic empirical application to electricity generation plants illustrate the utility of the proposed approach.

Keywords: vine copulas; production frontier; allocative inefficiency; technical inefficiency (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:demode:v:10:y:2022:i:1:p:145-158:n:5

DOI: 10.1515/demo-2022-0108

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