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Assessing the accuracy of efficiency rankings obtained from a stochastic frontier model

Author

Listed:
  • Nikolskiy, Ilya

    (Lomonosov Moscow State University, Moscow, Russian Federation)

  • Furmanov, Kirill

    (Central Economics and Mathematics Institute, RAS, Moscow, Russian Federation)

Abstract

A technique for assessing the concordance between true inefficiency of decision making units in a basic stochastic frontier model and their JLMS estimates is proposed. An approximate formula for Harrell’s C-index is derived for the case of half-normal distribution of inefficiency component. A simulation study shows that the approximation error is about 0.01 and that finite-sample values of Harrell’s C are lower than asymptotic values. Hence, the approximate formula may be considered as an upper bound for the ranking accuracy of the stochastic frontier model

Suggested Citation

  • Nikolskiy, Ilya & Furmanov, Kirill, 2023. "Assessing the accuracy of efficiency rankings obtained from a stochastic frontier model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 71, pages 128-142.
    • Handle: RePEc:ris:apltrx:0481
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    References listed on IDEAS

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    1. William Horrace & Seth Richards-Shubik & Ian Wright, 2015. "Expected efficiency ranks from parametric stochastic frontier models," Empirical Economics, Springer, vol. 48(2), pages 829-848, March.
    2. Afriat, Sidney N, 1972. "Efficiency Estimation of Production Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(3), pages 568-598, October.
    3. Roger B. Newson, 2010. "Comparing the predictive powers of survival models using Harrell’s C or Somers’ D," Stata Journal, StataCorp LP, vol. 10(3), pages 339-358, September.
    4. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    5. Valeriy Makarov & Albert Bakhtizin, 2014. "The Estimation Of The Regions’ Efficiency Of The Russian Federation Including The Intellectual Capital, The Characteristics Of Readiness For Innovation, Level Of Well-Being, And Quality Of Life," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 9-30.
    6. Ipatova, Irina, 2015. "The dynamics of total factor productivity and its components: Russian plastic production," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 21-40.
    7. Shchetynin, Yevhenii & Nazrullaeva, Eugenia, 2012. "Effects of fixed capital investments on technical efficiency in food industry," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 28(4), pages 63-84.
    8. Schmidt, Peter, 1976. "On the Statistical Estimation of Parametric Frontier Production Functions," The Review of Economics and Statistics, MIT Press, vol. 58(2), pages 238-239, May.
    9. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107029514, November.
    10. A. M. Theodoridis & A. Psychoudakis, 2008. "Efficiency Measurement in Greek Dairy Farms: Stochastic Frontier vs. Data Envelopment Analysis," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 1(2), pages 53-67, December.
    11. 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.
    12. 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.
    13. Golovan, Sergei, 2006. "Factors Influencing the Efficiency of the Russian Banks Performance," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 2(2), pages 3-17.
    14. 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.
    15. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    16. Kumbhakar,Subal C. & Lovell,C. A. Knox, 2003. "Stochastic Frontier Analysis," Cambridge Books, Cambridge University Press, number 9780521666633, November.
    17. K. Suresh Chandra & G. Gopal & M. Ramadurai, 2013. "A stochastic frontier approach to survival analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(6), pages 1362-1371, June.
    18. Richmond, J, 1974. "Estimating the Efficiency of Production," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(2), pages 515-521, June.
    19. Kirjavainen, Tanja, 2007. "Efficiency of Finnish Upper Secondary Schools: An Application of Stochastic Frontier Analysis with Panel Data," Discussion Papers 428, VATT Institute for Economic Research.
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    More about this item

    Keywords

    stochastic frontier; ranking; technical efficiency;
    All these keywords.

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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