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A Recursive Thick Frontier Approach To Estimating Production Efficiency

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Author Info
Rien Wagenvoort (European Investment Bank, Luxembourg)
Paul Schure () (Department of Economics, University of Northern B.C.)

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Abstract

We introduce a new panel data estimation technique for cost and production functions: the Recursive Thick Frontier Approach (RTFA). RTFA has two advantages over existing thick frontier methods. First, technical inefficiency is allowed to be dependent on the explanatory variables of the frontier model. Secondly, no distributional assumptions are imposed on the inefficiency component of the error term. We show by means of simulation experiments that RTFA can outperform the popular stochastic frontier approach (SFA) and the “within” OLS estimator for realistic parameterisations of the productivity model.

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File URL: http://web.uvic.ca/econ/research/papers/ewp0503.pdf
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Publisher Info
Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0503.

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Length: 26 pages
Date of creation: 11 Mar 2005
Date of revision:
Handle: RePEc:vic:vicewp:0503

Note: ISSN 1485-6441
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Related research
Keywords: Technical Efficiency; Efficiency Measurement; Frontier Production Functions; Recursive Thick Frontier Approach;

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
D2 - Microeconomics - - Production and Organizations

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References listed on IDEAS
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  1. Kalirajan, K P & Shand, R T, 1999. " Frontier Production Functions and Technical Efficiency Measures," Journal of Economic Surveys, Blackwell Publishing, vol. 13(2), pages 149-72, April. [Downloadable!] (restricted)
  2. 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. [Downloadable!] (restricted)
  3. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211. [Downloadable!] (restricted)
  4. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May. [Downloadable!] (restricted)
  5. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July. [Downloadable!] (restricted)
  6. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May. [Downloadable!] (restricted)
  7. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November. [Downloadable!] (restricted)
  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 238-39, May. [Downloadable!] (restricted)
  9. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163. [Downloadable!] (restricted)
  10. 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.
  11. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January. [Downloadable!] (restricted)
  12. Hinloopen, Jeroen & Wagenvoort, Rien, 1997. "On the computation and efficiency of a HBP-GM estimator some simulation results," Computational Statistics & Data Analysis, Elsevier, vol. 25(1), pages 1-15, July. [Downloadable!] (restricted)
  13. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April. [Downloadable!] (restricted)
  14. 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. [Downloadable!] (restricted)
  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. [Downloadable!] (restricted)
  16. Kalirajan, K P & Obwona, M B, 1994. "Frontier Production Function: The Stochastic Coefficients Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 56(1), pages 87-96, February.
  17. Allen N. Berger & David B. Humphrey, 1992. "Measurement and Efficiency Issues in Commercial Banking," NBER Chapters, in: Output Measurement in the Service Sectors, pages 245-300 National Bureau of Economic Research, Inc. [Downloadable!]
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