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A New Family of Copulas, with Application to Estimation of a Production Frontier System

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  • Amsler, Christine
  • Prokhorov, Artem
  • Schmidt, Peter
Abstract
In this paper we propose a new family of copulas for which the copula arguments are uncorrelated but dependent. Specifically, if w1 and w2 are the uniform random variables in the copula, they are uncorrelated, but w1 is correlated with |w2 - ½|. We show how this family of copulas can be applied to the error structure in an econometric production frontier model. We also generalize the family of copulas to three or more dimensions, and we give an empirical application.

Suggested Citation

  • Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2019. "A New Family of Copulas, with Application to Estimation of a Production Frontier System," Working Papers BAWP-2019-04, University of Sydney Business School, Discipline of Business Analytics.
    • Handle: RePEc:syb:wpbsba:2123/20203
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    References listed on IDEAS

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    1. Atkinson, Scott E & Cornwell, Christopher, 1994. "Parametric Estimation of Technical and Allocative Inefficiency with Panel Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(1), pages 231-243, February.
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    12. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
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    Cited by:

    1. Mamonov Mikhail E. & Parmeter Christopher F. & Prokhorov Artem B., 2022. "Dependence modeling in stochastic frontier analysis," Dependence Modeling, De Gruyter, vol. 10(1), pages 123-144, January.
    2. Alecos Papadopoulos, 2023. "The noise error component in stochastic frontier analysis," Empirical Economics, Springer, vol. 64(6), pages 2795-2829, June.
    3. 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.

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