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Technical and Economic Efficiency Measures under Short Run Profit Maximizing Behavior

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  • Laurens Cherchye

    (University of Leuven and Center for Economic Studies)

  • Timo Kuosmanen

    (Economic Research Unit, MTT Agrifood Research Finland)

  • Hervé Leleu

    (CNRS/LEM and IESEG School of Managment)

Abstract

The duality between measures of economic and technical efficiency has been extensively studied in the productive efficiency analysis. This duality ensures a meaningful interpretation of technical efficiency as economic efficiency evaluated at the most favourable shadow prices. This paper concentrates on economic efficiency as short run profit efficiency. We first argue that a modified version of Varian's goodness-of-it measure provides an appropriate economic efficiency measure in that context. Next, we show that a variant of the McFadden gauge function provides a natural dual efficiency measure for this short run profit efficiency measure. In particular we establish two attractive properties of that technical efficiency measure : (i) It can be interpreted as Varian's profit efficiency measure evaluated at shadow prices ; (ii) it provides an upper bound for profit efficiency

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Bibliographic Info

Paper provided by Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES) in its series Discussion Papers (REL - Recherches Economiques de Louvain) with number 2010022.

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Date of creation: 01 Jun 2010
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Handle: RePEc:ctl:louvre:2010022

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Keywords: Profit effiency; Technical efficiency; Technology distance functions;

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References

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  1. Rolf Färe & Shawna Grosskopf & Carl A Pasurka, Jr., 2001. "Accounting for Air Pollution Emissions in Measures of State Manufacturing Productivity Growth," Journal of Regional Science, Wiley Blackwell, vol. 41(3), pages 381-409.
  2. Timo Kuosmanen, 2003. "Duality Theory of Non-convex Technologies," Journal of Productivity Analysis, Springer, vol. 20(3), pages 273-304, November.
  3. Robert Russell, R., 1985. "Measures of technical efficiency," Journal of Economic Theory, Elsevier, vol. 35(1), pages 109-126, February.
  4. Varian, Hal R., 1990. "Goodness-of-fit in optimizing models," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 125-140.
  5. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
  6. Stéphane Blancard & Jean-Philippe Boussemart & Walter Briec & Kristiaan Kerstens, 2006. "Short- and Long-Run Credit Constraints in French Agriculture: A Directional Distance Function Framework Using Expenditure-Constrained Profit Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(2), pages 351-364.
  7. Bruce Domazlicky & William Weber, 2004. "Does Environmental Protection Lead to Slower Productivity Growth in the Chemical Industry?," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 28(3), pages 301-324, July.
  8. Salnykov, Mykhaylo & Zelenyuk, Valentin, 2005. "On the Commensurability of Directional Distance Functions," MPRA Paper 7068, University Library of Munich, Germany.
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Cited by:
  1. Laurens Cherchye & Bram De Rock, 2013. "The Economic Meaning of Data Envelopment Analysis: a "Behavioral" Perspective," Working Papers ECARES 2013/137577, ULB -- Universite Libre de Bruxelles.
  2. Kumbhakar, Subal C., 2013. "Specification and estimation of multiple output technologies: A primal approach," European Journal of Operational Research, Elsevier, vol. 231(2), pages 465-473.

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