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Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis

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Author Info

  • H. Fried

    ()

  • C. Lovell

    ()

  • S. Schmidt

    ()

  • S. Yaisawarng

    ()

Abstract

In this paper we propose a new technique for incorporating environmental effects and statistical noise into a producer performance evaluation based on data envelopment analysis (DEA). The technique involves a three-stage analysis. In the first stage, DEA is applied to outputs and inputs only, to obtain initial measures of producer performance. In the second stage, stochastic frontier analysis (SFA) is used to regress first stage performance measures against a set of environmental variables. This provides, for each input or output (depending on the orientation of the first stage DEA model), a three-way decomposition of the variation in performance into a part attributable to environmental effects, a part attributable to managerial inefficiency, and a part attributable to statistical noise. In the third stage, either inputs or outputs (again depending on the orientation of the first stage DEA model) are adjusted to account for the impact of the environmental effects and the statistical noise uncovered in the second stage, and DEA is used to re-evaluate producer performance. Throughout the analysis emphasis is placed on slacks, rather than on radial efficiency scores, as appropriate measures of producer performance. An application to nursing homes is provided to illustrate the power of the three-stage methodology. Copyright Kluwer Academic Publishers 2002

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File URL: http://hdl.handle.net/10.1023/A:1013548723393
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Bibliographic Info

Article provided by Springer in its journal Journal of Productivity Analysis.

Volume (Year): 17 (2002)
Issue (Month): 1 (January)
Pages: 157-174

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Handle: RePEc:kap:jproda:v:17:y:2002:i:1:p:157-174

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Web page: http://www.springerlink.com/link.asp?id=100296

Related research

Keywords: environmental effects; managerial inefficiency; statistical noise; slacks;

References

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  1. Simar, L. & Wilson, P.W., 1999. "Statistical Inference in Nonparametric Frontier Models: the State of the Art," Papers 9904, Catholique de Louvain - Institut de statistique.
  2. 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.
  3. 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.
  4. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
  5. 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.
  6. Fried, Harold O. & Knox Lovell, C. A. & Eeckaut, Philippe Vanden, 1993. "Evaluating the performance of US credit unions," Journal of Banking & Finance, Elsevier, vol. 17(2-3), pages 251-265, April.
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