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Efficiency analysis in the presence of uncertainty

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Author Info

  • Christopher O’Donnell

    ()

  • Robert Chambers

    ()

  • John Quiggin

    ()

Abstract

In a stochastic decision environment, differences in information can lead rational decision makers facing the same stochastic technology and the same markets to make different production choices. Efficiency and productivity measurement in such a setting can be seriously and systematically biased by the manner in which the stochastic technology is represented. For example, conventional production frontiers implicitly impose the restriction that information differences have no effect on the way risk-neutral decision makers utilize the same input bundle. The result is that rational and efficient ex ante production choices can be mistakenly characterized as inefficient -- informational differences are mistaken for differences in technical efficiency. This paper uses simulation methods to illustrate the type and magnitude of empirical errors that can emerge in efficiency analysis as a result of overly restrictive representations of production technologies.

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File URL: http://hdl.handle.net/10.1007/s11123-009-0143-9
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Bibliographic Info

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

Volume (Year): 33 (2010)
Issue (Month): 1 (February)
Pages: 1-17

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Handle: RePEc:kap:jproda:v:33:y:2010:i:1:p:1-17

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

Related research

Keywords: Uncertainty; Efficiency measurement; Data envelopment analysis; Stochastic frontier analysis; C21; D21; D24; D81;

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References

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  1. Nauges, Celine & O'Donnell, Christopher J. & Quiggin, John C., 2009. "Uncertainty and technical efficiency in Finnish Agriculture," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 48062, Australian Agricultural and Resource Economics Society.
  2. Coelli, Tim & Perelman, Sergio, 1999. "A comparison of parametric and non-parametric distance functions: With application to European railways," European Journal of Operational Research, Elsevier, vol. 117(2), pages 326-339, September.
  3. Battese, G. E. & Rambaldi, A. N. & Wan, G. H., 1995. "A Stochastic Frontier Production Function with Flexible Risk Properties," 1995 Conference (39th), February 14-16, 1995, Perth, Australia 148840, Australian Agricultural and Resource Economics Society.
  4. Powell, Alan A. & Gruen, Fred H.G., 1967. "The Estimation Of Production Frontiers: The Australian Livestock/Cereals Complex," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 11(01), June.
  5. C.J. O'Donnell & W.E. Griffiths, 2004. "Estimating State-Contingent Production Frontiers," Department of Economics - Working Papers Series 911, The University of Melbourne.
  6. Subal C. Kumbhakar, 2002. "Specification and Estimation of Production Risk, Risk Preferences and Technical Efficiency," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(1), pages 8-22.
  7. Gong, Linguo & Sun, Bruce, 1995. "Efficiency measurement of production operations under uncertainty," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 55-66, April.
  8. Robert G. Chambers & John Quiggin, 1998. "Cost Functions and Duality for Stochastic Technologies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(2), pages 288-295.
  9. Chambers,Robert G. & Quiggin,John, 2000. "Uncertainty, Production, Choice, and Agency," Cambridge Books, Cambridge University Press, number 9780521622448, October.
  10. O. B. Olesen & N. C. Petersen, 1995. "Chance Constrained Efficiency Evaluation," Management Science, INFORMS, vol. 41(3), pages 442-457, March.
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