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Stochastic frontier models with threshold efficiency

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  • Sungwon Lee
  • Young Lee

Abstract

This paper proposes a tail-truncated stochastic frontier model that allows for the truncation of technical efficiency from below. The truncation bound implies the inefficiency threshold for survival. Specifically, this paper assumes a uniform distribution of technical inefficiency and derives the likelihood function. Even though this distributional assumption imposes a strong restriction that technical inefficiency has a uniform probability density over [0, θ], where θ is the threshold parameter, this model has two advantages: (1) the reduction in the number of parameters compared with more complicated tail-truncated models allows better performance in numerical optimization; and (2) it is useful for empirical studies of the distribution of efficiency or productivity, particularly the truncation of the distribution. The Monte Carlo simulation results support the argument that this model approximates the distribution of inefficiency precisely, as the data-generating process not only follows the uniform distribution but also the truncated half-normal distribution if the inefficiency threshold is small. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Sungwon Lee & Young Lee, 2014. "Stochastic frontier models with threshold efficiency," Journal of Productivity Analysis, Springer, vol. 42(1), pages 45-54, August.
  • Handle: RePEc:kap:jproda:v:42:y:2014:i:1:p:45-54
    DOI: 10.1007/s11123-013-0364-9
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    1. Timothy Dunne & Shawn Klimek & James Schmitz, Jr., 2010. "Competition and Productivity: Evidence from the Post WWII U.S. Cement Industry," Working Papers 10-29, Center for Economic Studies, U.S. Census Bureau.
    2. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    3. David Good & M. Nadiri & Lars-Hendrik Röller & Robin Sickles, 1993. "Efficiency and productivity growth comparisons of European and U.S. Air carriers: A first look at the data," Journal of Productivity Analysis, Springer, vol. 4(1), pages 115-125, June.
    4. Amemiya, Takeshi, 1973. "Regression Analysis when the Dependent Variable is Truncated Normal," Econometrica, Econometric Society, vol. 41(6), pages 997-1016, November.
    5. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 2008. "The Measurement of Productive Efficiency and Productivity Growth," OUP Catalogue, Oxford University Press, number 9780195183528.
    6. Chad Syverson, 2004. "Market Structure and Productivity: A Concrete Example," Journal of Political Economy, University of Chicago Press, vol. 112(6), pages 1181-1222, December.
    7. 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.
    8. David A. Matsa, 2011. "Competition and Product Quality in the Supermarket Industry," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(3), pages 1539-1591.
    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. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    11. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    12. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    13. Qu Feng & William C. Horrace, 2012. "Alternative technical efficiency measures: Skew, bias and scale," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 253-268, March.
    14. Thomas J. Holmes & James A. Schmitz, 2010. "Competition and Productivity: A Review of Evidence," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 619-642, September.
    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.
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    1. Young Hoon Lee & Hayley Jang & Sun Ho Hwang, 2015. "Market Competition and Threshold Efficiency in the Sports Industry," Journal of Sports Economics, , vol. 16(8), pages 853-870, December.

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    More about this item

    Keywords

    Stochastic frontier; Technical efficiency; Threshold inefficiency; Uniform distribution; Productivity distribution; C13; C21; D24; L11;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

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