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Measuring potential gains from specialization under non-convex technologies

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  • S Blancard

    (AGROSUP Dijon, CESAER, Dijon, France)

  • J-P Boussemart

    (University of Lille and LEM-I�SEG School of Management, Lille, France)

  • H Leleu

    (CNRS-LEM and I�SEG School of Management, Lille, France)

Abstract

In this paper, the Free Coordination Hull (FCH) approach developed by Green and Cook (2004) is combined with the Free Disposal Hull (FDH) model to detect potential gains from specialization. As a non-convex approach that allows both directly observed and summed Decision Making Units to define the production technology, FCH is the relevant model for analysing optimal reallocation of activity among smaller and more specialized units. Indeed in more traditional Data Envelopment Analysis models the convexity assumption precludes the possibility of detecting potential gains from specialization and can only reveal economies of scope. Therefore non-convex technologies are required to model diseconomies of scope. On the basis of FDH and FCH technologies, an overall efficiency measure is decomposed into three components, namely: technical, size and specialization efficiencies. A 2003 database of French farms is used as an illustration. Results indicate that input inefficiency in the agricultural sector is mainly driven by a lack of specialization, which represents approximately 50% of the overall inefficiency.

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Article provided by Palgrave Macmillan in its journal Journal of the Operational Research Society.

Volume (Year): 62 (2011)
Issue (Month): 10 (October)
Pages: 1871-1880

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Handle: RePEc:pal:jorsoc:v:62:y:2011:i:10:p:1871-1880

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  1. Wu, Shunxiang & Prato, Anthony A., 2006. "Cost Efficiency and Scope Economies of Crop and Livestock Farms in Missouri," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 38(03), December.
  2. M. J. Farrell, 1959. "The Convexity Assumption in the Theory of Competitive Markets," Journal of Political Economy, University of Chicago Press, vol. 67, pages 377.
  3. Chavas, Jean-Paul & Aliber, Michael, 1993. "An Analysis Of Economic Efficiency In Agriculture: A Nonparametric Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(01), July.
  4. 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.
  5. Bogetoft, Peter & Wang, Dexiang, 2003. "Estimating the Potential Gains from Mergers," Unit of Economics Working papers 24213, Royal Veterinary and Agricultural University, Food and Resource Economic Institute.
  6. Panzar, John C & Willig, Robert D, 1981. "Economies of Scope," American Economic Review, American Economic Association, vol. 71(2), pages 268-72, May.
  7. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
  8. Maindiratta, Ajay, 1990. "Largest size-efficient scale and size efficiencies of decision-making units in data envelopment analysis," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 57-72.
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