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Oriented stochastic data envelopment models: Ranking comparison to stochastic frontier approach

  • Frantisek Brazdik

Results of data envelopment analysis sensitively respond to stochastic noise in the data. In this paper, by introduction of output augmentation and input reduction I extend additive models for stochastic data envelopment analysis (SDEA), which were developed by Li (1998) to handle the noise in the data. Applying the linearization procedure by Li (1998) the linearized versions of models are derived. In the empirical part of this work, the effi- ciency scores of Indonesian rice farms are computed. The computed scores are compared to the stochastic frontier approach scores by Druska and Horrace (2004) and weak ranking consistency with results of stochastic frontier method is observed.

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Paper provided by The Center for Economic Research and Graduate Education - Economic Institute, Prague in its series CERGE-EI Working Papers with number wp271.

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Date of creation: Aug 2005
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Handle: RePEc:cer:papers:wp271
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  1. Abdul Wadud & Ben White, 2000. "Farm household efficiency in Bangladesh: a comparison of stochastic frontier and DEA methods," Applied Economics, Taylor & Francis Journals, vol. 32(13), pages 1665-1673.
  2. Viliam Druska & William C. Horrace, 2002. "Generalized Moments Estimation for Spatial Panel Data: Indonesian Rice Farming," Econometrics 0206004, EconWPA, revised 11 May 2003.
  3. Halme, Merja & Korhonen, Pekka, 2000. "Restricting weights in value efficiency analysis," European Journal of Operational Research, Elsevier, vol. 126(1), pages 175-188, October.
  4. 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.
  5. William Cooper & Zhimin Huang & Vedran Lelas & Susan Li & Ole Olesen, 1998. "Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA," Journal of Productivity Analysis, Springer, vol. 9(1), pages 53-79, January.
  6. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA.
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