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A Note on Theory of Productive Efficiency and Stochastic Frontier Models

  • Aikaterini Kokkinou
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    Neoclassical economics assume that producers in an economy always operate efficiently, however in real terms, producers are not always fully efficient. This difference may be explained both in terms of efficiency, as well as unforeseen exogenous shocks outside the producer control. This paper aims to analyse the productive efficiency estimation through a stochastic frontier analysis approach. Particularly, this paper attempts to examine systematically the theoretical background of stochastic frontier function estimation, focusing on the analysis of the efficiency function, in order to provide a solid background for productive efficiency estimation.

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    File URL: http://www.ersj.eu/repec/ers/papers/10_4_p7.pdf
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    Article provided by European Research Studies Journal in its journal European Research Studies Journal.

    Volume (Year): XIII (2010)
    Issue (Month): 4 ()
    Pages: 109-118

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    Handle: RePEc:ers:journl:v:xiii:y:2010:i:4:p:109-118
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    1. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-74, October.
    2. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    3. K.P. Kalirajan & R.T. Shand, 1992. "Causality between Technical and Allocative Efficiencies: An Empirical Testing," Journal of Economic Studies, Emerald Group Publishing, vol. 19(2), pages 3-17, May.
    4. Schmidt, Peter & Knox Lovell, C. A., 1979. "Estimating technical and allocative inefficiency relative to stochastic production and cost frontiers," Journal of Econometrics, Elsevier, vol. 9(3), pages 343-366, February.
    5. 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 435-44, June.
    6. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    7. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
    8. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(03), December.
    9. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    10. Kalirajan, K P & Shand, R T, 1999. " Frontier Production Functions and Technical Efficiency Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 13(2), pages 149-72, April.
    11. 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.
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