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

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.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Technical and allocative inefficiency in production systems: a vine copula approach ; volume:10 ; number:1 ; year:2022 ; pages:145-158 ; extent:14 ; Dependence modeling ; 10, Heft 1 (2022), 145-158 (gesamt 14)

Beteiligte, Orts- und Zeitangaben

• Urheber: Zhai, Jian ; James, Robert ; Prokhorov, Artem

Weitere Informationen

• DOI: 10.1515/demo-2022-0108
• URN: urn:nbn:de:101:1-2022072714115810198287
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:24 MESZ