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

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Listed:
  • 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)

  • Prokhorov Artem

    (Discipline of Business Analytics, Business School, University of Sydney, Sydney, Australia)

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.

Suggested Citation

  • Zhai Jian & James Robert & Prokhorov Artem, 2022. "Technical and allocative inefficiency in production systems: a vine copula approach," Dependence Modeling, De Gruyter, vol. 10(1), pages 145-158, January.
    • Handle: RePEc:vrs:demode:v:10:y:2022:i:1:p:145-158:n:5
    DOI: 10.1515/demo-2022-0108
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    References listed on IDEAS

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