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Efficiency and Global Scale Characteristics on the “No Free Lunch” Assumption Only

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  • Victor Podinovski

Abstract

In a production technology, the type of returns to scale (RTS) associated with an efficient decision making unit (DMU) is indicative of the direction of marginal rescaling that the DMU should undertake in order to improve its productivity. In this paper a concept of global returns to scale (GRS) is developed as an indicator of the direction in which the most productive scale size (MPSS) of an efficient DMU is achieved. The GRS classes are useful in assisting strategic decisions like those involving mergers of units or splitting into smaller firms. The two characterisations, RTS and GRS, are the same in a convex technology but generally different in a non-convex one. It is shown that, in a non-convex technology, the well-known method of testing RTS proposed by Färe et al. is in fact testing for GRS and not RTS. Further, while there are three types of RTS: constant, decreasing and increasing (CRS, DRS and IRS, respectively), the classification according to GRS includes the fourth type of sub-constant GRS, which describes a DMU able to achieve its MPSS by both reducing and increasing the scale of operations. The notion of GRS is applicable to a wide range of technologies, including the free disposal hull (FDH) and all polyhedral technologies used in data envelopment analysis (DEA). Copyright Kluwer Academic Publishers 2004

Suggested Citation

  • Victor Podinovski, 2004. "Efficiency and Global Scale Characteristics on the “No Free Lunch” Assumption Only," Journal of Productivity Analysis, Springer, vol. 22(3), pages 227-257, November.
  • Handle: RePEc:kap:jproda:v:22:y:2004:i:3:p:227-257
    DOI: 10.1007/s11123-004-7575-z
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    1. Kerstens, Kristiaan & Vanden Eeckaut, Philippe, 1999. "Estimating returns to scale using non-parametric deterministic technologies: A new method based on goodness-of-fit," European Journal of Operational Research, Elsevier, vol. 113(1), pages 206-214, February.
    2. Kuosmanen, Timo, 2001. "DEA with efficiency classification preserving conditional convexity," European Journal of Operational Research, Elsevier, vol. 132(2), pages 326-342, July.
    3. Dekker, David & Post, Thierry, 2001. "A quasi-concave DEA model with an application for bank branch performance evaluation," European Journal of Operational Research, Elsevier, vol. 132(2), pages 296-311, July.
    4. Walter Briec & Kristiaan Kerstens & Hervé Leleu & Philippe Eeckaut, 2000. "Returns to Scale on Nonparametric Deterministic Technologies: Simplifying Goodness-of-Fit Methods Using Operations on Technologies," Journal of Productivity Analysis, Springer, vol. 14(3), pages 267-274, November.
    5. Timo Kuosmanen, 2003. "Duality Theory of Non-convex Technologies," Journal of Productivity Analysis, Springer, vol. 20(3), pages 273-304, November.
    6. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    7. Baumol, William J, 1982. "Contestable Markets: An Uprising in the Theory of Industry Structure," American Economic Review, American Economic Association, vol. 72(1), pages 1-15, March.
    8. AGRELL, Per J. & BOGETOFT, Peter & BROCK, Michael & TIND, Jorgen, 2005. "Efficiency evaluation with convex pairs," LIDAM Reprints CORE 1828, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Niels Christian Petersen, 1990. "Data Envelopment Analysis on a Relaxed Set of Assumptions," Management Science, INFORMS, vol. 36(3), pages 305-314, March.
    10. 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.
    11. Podinovski, V. V., 2005. "Selective convexity in DEA models," European Journal of Operational Research, Elsevier, vol. 161(2), pages 552-563, March.
    12. repec:cor:louvrp:-1828 is not listed on IDEAS
    13. Banker, Rajiv D. & Cooper, William W. & Seiford, Lawrence M. & Thrall, Robert M. & Zhu, Joe, 2004. "Returns to scale in different DEA models," European Journal of Operational Research, Elsevier, vol. 154(2), pages 345-362, April.
    14. Peter Bogetoft & Joseph M. Tama & Jørgen Tind, 2000. "Convex Input and Output Projections of Nonconvex Production Possibility Sets," Management Science, INFORMS, vol. 46(6), pages 858-869, June.
    15. Seiford, Lawrence M. & Zhu, Joe, 1999. "An investigation of returns to scale in data envelopment analysis," Omega, Elsevier, vol. 27(1), pages 1-11, February.
    16. Banker, Rajiv D. & Chang, Hsihui & Cooper, William W., 1996. "Equivalence and implementation of alternative methods for determining returns to scale in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 89(3), pages 473-481, March.
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    2. Zafar, Sohail & Ahmed, Vaqar, 2009. "External scale economies in manufacturing sector of Pakistan: a comparison of large scale manufacturing sector of Sindh and Punjab," MPRA Paper 17665, University Library of Munich, Germany.
    3. Hennebel, Veerle & Simper, Richard & Verschelde, Marijn, 2017. "Is there a prison size dilemma? An empirical analysis of output-specific economies of scale," European Journal of Operational Research, Elsevier, vol. 262(1), pages 306-321.
    4. Giovanni Cesaroni & Kristiaan Kerstens & Ignace Van de Woestyne, 2017. "Estimating scale economies in non-convex production models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(11), pages 1442-1451, November.
    5. Cesaroni, Giovanni & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2017. "Global and local scale characteristics in convex and nonconvex nonparametric technologies: A first empirical exploration," European Journal of Operational Research, Elsevier, vol. 259(2), pages 576-586.
    6. Cesaroni, Giovanni & Giovannola, Daniele, 2015. "Average-cost efficiency and optimal scale sizes in non-parametric analysis," European Journal of Operational Research, Elsevier, vol. 242(1), pages 121-133.
    7. Ando, Kazutoshi & Minamide, Masato & Sekitani, Kazuyuki & Shi, Jianming, 2017. "Monotonicity of minimum distance inefficiency measures for Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 260(1), pages 232-243.

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