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Efficient Semiparametric Estimation in Stochastic Frontier Model

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Author Info

  • Park, B.U.
  • Simar, L.

Abstract

This paper considers the semiparametric stochastic frontier model with panel data which arises in the problem of measuring technical inefficiency in production processes. We assume a parametric form for the frontier function, which is linear in production inputs. The density of the individual firm-specific effects is considered unknown. We construct an efficient estimator of the slope parameters in the frontier function . We also give an estimator of the level of the frontier function and its asymptotic properties are investigated. Furthermore, we provide a predictor of the individual effects which can be directly translated to firm-specific technical inefficiencies. Finally, we illustrate our methods through a real data example.

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Bibliographic Info

Paper provided by Catholique de Louvain - Institut de statistique in its series Papers with number 9201.

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Length: 22 pages
Date of creation: 1992
Date of revision:
Handle: RePEc:fth:louvis:9201

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Postal: Universite Catholique de Louvain, Institut de Statistique, Voie du Roman Pays, 34 B-1348 Louvain- La-Neuve, Belgique.

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Keywords: evaluation ; econometrics;

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Cited by:
  1. Gholamreza Hajargasht, 2003. "Semiparametric Estimation of Stochastic Frontiers A Bayesian Penalized Approach," CEPA Working Papers Series WP042003, School of Economics, University of Queensland, Australia.
  2. Myungsup Kim & Yangseon Kim & Peter Schmidt, 2006. "On the Accuracy of Bootstrap Confidence Intervals for Efficiency Levels in Stochastic Frontier Models with Panel Data," Working Papers 0704, University of Crete, Department of Economics.
  3. Byeong U. Park & Robin C Sickles & Léopold Simar, 2002. "Semi parametric efficient estimation of dynamic panel data models," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C6-1, International Conferences on Panel Data.
  4. Park, Byeong U. & Sickles, Robin C. & Simar, Leopold, 2003. "Semiparametric-efficient estimation of AR(1) panel data models," Journal of Econometrics, Elsevier, vol. 117(2), pages 279-309, December.
  5. Jim E. Griffin & Mark F.J. Steel, 2002. "Semiparametric Bayesian Inference for Stochastic Frontier Models," Econometrics 0209001, EconWPA, revised 18 Sep 2002.
  6. Bouezmarni, Taoufik & Rombouts, Jeroen V.K., 2010. "Nonparametric density estimation for positive time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 245-261, February.
  7. Tai-Hsin Huang & Tong-Liang Kao, 2006. "Joint estimation of technical efficiency and production risk for multi-output banks under a panel data cost frontier model," Journal of Productivity Analysis, Springer, vol. 26(1), pages 87-102, August.
  8. William C. Horrace & Peter Schmidt, 2000. "Multiple comparisons with the best, with economic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 1-26.
  9. Paul A. Bekker & E. C. Leertouwer, 2000. "Exact Inference for the Linear Model with Groupwise Heteroscedasticity," Econometric Society World Congress 2000 Contributed Papers 1760, Econometric Society.
  10. Bekker, Paul A., 2002. "Exact inference for the linear model with groupwise heteroscedastic spherical disturbances," Journal of Econometrics, Elsevier, vol. 111(2), pages 285-302, December.
  11. I. Fraser & W. Horrace, 2003. "Technical Efficiency of Australian Wool Production: Point and Confidence Interval Estimates," Journal of Productivity Analysis, Springer, vol. 20(2), pages 169-190, September.
  12. Byeong Park & Seuck Song, 2007. "Comments on: Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 16(1), pages 47-51, May.
  13. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA.
  14. Panutat Satchachai & Peter Schmidt, 2010. "Estimates of technical inefficiency in stochastic frontier models with panel data: generalized panel jackknife estimation," Journal of Productivity Analysis, Springer, vol. 34(2), pages 83-97, October.

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