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Efficient semiparametric estimation in stochastic frontier model

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  • PARK, Byeong

    (CORE and Institut of Statistics, Université catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium)

  • SIMAR, Léopold

    (CORE and Institut of Statistics, Université catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium)

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 Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 1992013.

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Date of creation: 01 Feb 1992
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Handle: RePEc:cor:louvco:1992013

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Related research

Keywords: Stochastic frontier model; semiparametric model; efficient estimation; information bound; panel data;

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Cited by:
  1. 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.
  2. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
  3. Jim E. Griffin & Mark F.J. Steel, 2002. "Semiparametric Bayesian Inference for Stochastic Frontier Models," Econometrics 0209001, EconWPA, revised 18 Sep 2002.
  4. Iain Fraser & William C. Horrace, 2002. "Technical Efficiency of Australian Wool Production: Point and Confidence Interval Estimates," Public Economics 0206001, EconWPA, revised 11 May 2003.
  5. Park, B.U. & Sickles, R.C. & Simar, L., 2000. "Semiparametric Efficient Estimation of AR(1) Panel Data Models," Papers 0020, Catholique de Louvain - Institut de statistique.
  6. 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.
  7. 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.
  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. 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.
  10. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA.
  11. 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.
  12. Gholamreza Hajargasht, 2003. "Semiparametric Estimation of Stochastic Frontiers A Bayesian Penalized Approach," CEPA Working Papers Series WP042003, School of Economics, University of Queensland, Australia.
  13. 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.

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