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Analysis of dependence between the random components of a stochastic production function for the purpose of technical efficiency estimation

Listed author(s):
  • Aivazian, Sergei

    ()

    (CEMI RAS, Moscow, Russia)

  • Afanasiev, Mikhail

    ()

    (CEMI RAS, Moscow, Russia)

  • Rudenko, Victoria

    ()

    (Moscow Engineering Physics Institute (National Research Nuclear University), Russia)

In elaboration of the stochastic frontier methodology we offer an approach to test a statistic hypothesis about independence of random components of a stochastic production function for the purpose of estimation of technical efficiency. We describe the dependence between the error components by a copula. For parameters estimation in the econometric model in case of dependent error components the analytical expressions for log-likelihood function and its derivatives are given. The results of an experimental hypothesis test based on simulated data with dependent error components are also provided. We use two approaches for the parameters estimation: statistical package Stata 10.0 under an assumption of independence of the error components and created in MS Excel macro which gives the possibility to analyze models with dependent error components. It is shown that using non-tested assumption of independence of the random components of a stochastic production function may lead to wrong results in estimation of the technical efficiency.

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File URL: http://pe.cemi.rssi.ru/pe_2014_2_03-18.pdf
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Article provided by Publishing House "SINERGIA PRESS" in its journal Applied Econometrics.

Volume (Year): 34 (2014)
Issue (Month): 2 ()
Pages: 3-18

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Handle: RePEc:ris:apltrx:0234
Contact details of provider: Web page: http://appliedeconometrics.cemi.rssi.ru/

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  1. Christine Amsler & Artem Prokhorov & Peter Schmidt, 2014. "Using Copulas to Model Time Dependence in Stochastic Frontier Models," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 497-522, August.
  2. Hung-pin Lai & Cliff Huang, 2013. "Maximum likelihood estimation of seemingly unrelated stochastic frontier regressions," Journal of Productivity Analysis, Springer, vol. 40(1), pages 1-14, August.
  3. Murray D. Smith, 2008. "Stochastic frontier models with dependent error components," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 172-192, March.
  4. Penikas, Henry & Simakova, Varvara, 2009. "Interest Rate Risk Management Based on Copula-GARCH Models," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 13(1), pages 3-36.
  5. Rosenberg, Joshua V. & Schuermann, Til, 2006. "A general approach to integrated risk management with skewed, fat-tailed risks," Journal of Financial Economics, Elsevier, vol. 79(3), pages 569-614, March.
  6. Aigner, D J & Amemiya, Takeshi & Poirier, Dale J, 1976. "On the Estimation of Production Frontiers: Maximum Likelihood Estimation of the Parameters of a Discontinuous Density Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 17(2), pages 377-396, June.
  7. Christian Genest & Bruno Rémillard, 2004. "Test of independence and randomness based on the empirical copula process," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 13(2), pages 335-369, December.
  8. Blagoveschensky, Yury, 2012. "Basics of copula’s theory," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 26(2), pages 113-130.
  9. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
  10. 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.
  11. Aivazian, Sergei & Afanasiev, Mikhail & Rudenko, Victoria, 2012. "Some specification aspects for three-factor models of a company's production potential taking into account intellectual capital," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 27(3), pages 36-69.
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