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Are all scales optimal in Dea? Theory and empirical evidence

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  • Lennart Hjalmarsson

    ()

  • Finn R. Førsund

    ()

Abstract

Policy recommendations concerning optimal scale of production units often have serious implications for the restructuring of a sector, while tests of natural monopoly have important implications for regulatory structure. The piecewise linear frontier production function framework is becoming the most popular one for assessing not only technical efficiency of operations, but also for scale efficiency and calculation of optimal scale sizes. The main purpose of the present study is to check if neoclassical production theory gives any guidance as to the nature of scale properties in the DEA model, and to empirically investigate such properties. The empirical results indicate that optimal scale may be found over almost the entire size variations in outputs and inputs, thus making policy recommendations about scale efficiency dubious. It is necessary to establish the nature of optimal scale before any practical use can be made. Proposals for such indexes that should be calculated are provided.

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Bibliographic Info

Paper provided by ICER - International Centre for Economic Research in its series ICER Working Papers with number 14-2002.

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Length: 26 pages
Date of creation: Feb 2002
Date of revision:
Handle: RePEc:icr:wpicer:14-2002

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Keywords: Optimal scale; scale elasticity; data envelopment analysis (DEA); frontier production functions; duals;

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  1. Jamasb, T. & Pollitt, M., 2000. "Benchmarking and regulation: international electricity experience," Utilities Policy, Elsevier, vol. 9(3), pages 107-130, September.
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  7. Banker, R. D. & Bardhan, I. & Cooper, W. W., 1996. "A note on returns to scale in DEA," European Journal of Operational Research, Elsevier, vol. 88(3), pages 583-585, February.
  8. McFadden, Daniel, 1978. "Cost, Revenue, and Profit Functions," Histoy of Economic Thought Chapters, in: Fuss, Melvyn & McFadden, Daniel (ed.), Production Economics: A Dual Approach to Theory and Applications, volume 1, chapter 1 McMaster University Archive for the History of Economic Thought.
  9. Banker, Rajiv D., 1984. "Estimating most productive scale size using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 17(1), pages 35-44, July.
  10. Kim, H Youn, 1987. "Economies of Scale in Multi-product Firms: An Empirical Analysis," Economica, London School of Economics and Political Science, vol. 54(214), pages 185-206, May.
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Cited by:
  1. Erbetta, Fabrizio & Rappuoli, Luca, 2008. "Optimal scale in the Italian gas distribution industry using data envelopment analysis," Omega, Elsevier, vol. 36(2), pages 325-336, April.
  2. Olesen, Ole B. & Ruggiero, John, 2014. "Maintaining the Regular Ultra Passum Law in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 235(3), pages 798-809.
  3. Førsund, Finn R. & Kittelsen, Sverre A.C & Lindseth, Frode, 2005. "Efficiency And Productivity Of Norwegian Tax Offices," Memorandum 29/2005, Oslo University, Department of Economics.
  4. Finn R. Førsund & Nikias Sarafoglou, 2005. "The Tale of Two research Communities: The Diffusion of Research on Productive Efficiency," Department of Economics University of Siena 446, Department of Economics, University of Siena.
  5. Kaoru Tone & Miki Tsutsui, 2013. "How to deal with S-shaped curve in DEA," GRIPS Discussion Papers 13-10, National Graduate Institute for Policy Studies.
  6. Tone, Kaoru & Sahoo, Biresh K., 2004. "Degree of scale economies and congestion: A unified DEA approach," European Journal of Operational Research, Elsevier, vol. 158(3), pages 755-772, November.
  7. Olesen, Ole Bent & Petersen, Niels Christian, 2013. "Imposing the Regular Ultra Passum law in DEA models," Omega, Elsevier, vol. 41(1), pages 16-27.
  8. Førsund , Finn R. & Kittelsen , Sverre A. & Krivonozhko , Vladimir E., 2007. "Farrell Revisited: Visualising the DEA Production Frontier," Memorandum 15/2007, Oslo University, Department of Economics.

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