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Stochastic Frontier Models With Correlated Error Components

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  • Murray D Smith
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    Abstract

    In the productivity modelling literature, the disturbances U (representing technical inefficiency) and V (representing noise) of the composite error W=V-U of the stochastic frontier model are assumed to be independent random variables. By employing the copula approach to statistical modelling, the joint behaviour of U and V can be parameterised thereby allowing the data the opportunity to determine the adequacy of the independence assumption. In this context, three examples of the copula approach are given: the first is algebraic (the Logistic-Exponential stochastic frontier model with margins bound by the Fairlie-Gumbel-Morgenstern copula) and the second and third are empirically oriented, using data sets well-known in productivity analysis. Analysed are a cross-section of cost data sampled from the US electrical power industry, and an unbalanced panel of data sampled from the US airline industry

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    File URL: http://repec.org/esAUSM04/up.4826.1077439277.pdf
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    Bibliographic Info

    Paper provided by Econometric Society in its series Econometric Society 2004 Australasian Meetings with number 121.

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    Date of creation: 11 Aug 2004
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    Handle: RePEc:ecm:ausm04:121

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    Related research

    Keywords: Stochastic Frontier model; Copula; Copula approach; Sklar's theorem; Families of copulas; Spearman's rho.;

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    1. Valentino Dardanoni & Peter Lambert, 1998. "Horizontal inequity comparisons," IFS Working Papers W98/07, Institute for Fiscal Studies.
    2. Fang, Hong-Bin & Fang, Kai-Tai & Kotz, Samuel, 2002. "The Meta-elliptical Distributions with Given Marginals," Journal of Multivariate Analysis, Elsevier, vol. 82(1), pages 1-16, July.
    3. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    4. Miller, Douglas J. & Liu, Wei-han, 2002. "On the recovery of joint distributions from limited information," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 259-274, March.
    5. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    6. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    7. Murray D. Smith, 2003. "Modelling sample selection using Archimedean copulas," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 99-123, 06.
    8. Luis R. Murillo-Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, 02.
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    Cited by:
    1. Bandyopadhyay, Debdas & Das, Arabinda, 2007. "Identifiability of the Stochastic Frontier Models," MPRA Paper 8032, University Library of Munich, Germany, revised Jan 2008.
    2. Debdas Bandyopadhyay & Arabinda Das, 2006. "On measures of technical inefficiency and production uncertainty in stochastic frontier production model with correlated error components," Journal of Productivity Analysis, Springer, vol. 26(2), pages 165-180, October.

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