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Modelling multi-output stochastic frontiers using copulas

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  • Carta, Alessandro
  • Steel, Mark F.J.

Abstract

The aim is to introduce a new econometric methodology for multi-output production frontiers. In the context of a system of frontier equations, a flexible multivariate distribution for the inefficiency error term is used. This multivariate distribution is constructed through a copula function which allows for separate modelling of the marginal inefficiency distributions and the dependence. Specific attention to the elicitation of a sensible (improper) prior is paid and simple sufficient conditions for posterior propriety are provided. Inference is conducted through a Markov chain Monte Carlo sampler. Bayes factors are used to compare various copula specifications in the empirical context of Dutch dairy farm data, with two outputs.

Suggested Citation

  • Carta, Alessandro & Steel, Mark F.J., 2012. "Modelling multi-output stochastic frontiers using copulas," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3757-3773.
  • Handle: RePEc:eee:csdana:v:56:y:2012:i:11:p:3757-3773
    DOI: 10.1016/j.csda.2010.07.007
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    References listed on IDEAS

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    Cited by:

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    2. Graziella Bonanno & Domenico De Giovanni & Filippo Domma, 2017. "The ‘wrong skewness’ problem: a re-specification of stochastic frontiers," Journal of Productivity Analysis, Springer, vol. 47(1), pages 49-64, February.
    3. Tai-Hsin Huang & Nan-Hung Liu & Subal C. Kumbhakar, 2018. "Joint estimation of the Lerner index and cost efficiency using copula methods," Empirical Economics, Springer, vol. 54(2), pages 799-822, March.
    4. Huang, Tai-Hsin & Lin, Chung-I & Chen, Kuan-Chen, 2017. "Evaluating efficiencies of Chinese commercial banks in the context of stochastic multistage technologies," Pacific-Basin Finance Journal, Elsevier, vol. 41(C), pages 93-110.
    5. Aivazian, Sergei & Afanasiev, Mikhail & Rudenko, Victoria, 2014. "Analysis of dependence between the random components of a stochastic production function for the purpose of technical efficiency estimation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 34(2), pages 3-18.
    6. Huang, Tai-Hsin & Chen, Kuan-Chen & Lin, Chung-I, 2018. "An extension from network DEA to copula-based network SFA: Evidence from the U.S. commercial banks in 2009," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 51-62.
    7. Huang, Tai-Hsin & Hu, Chu-Nan & Chang, Bao-Guang, 2018. "Competition, efficiency, and innovation in Taiwan’s banking industry — An application of copula methods," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 362-375.

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