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Shadow profit maximization and a measure of overall inefficiency

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  • Subhash Ray

Abstract

Determining the profit maximizing input–output bundle of a firm requires data on prices. This paper shows how endogenously determined shadow prices can be used in place of actual prices to obtain the optimal input–output bundle where the firm’s shadow profit is maximized. This approach amounts to an application of the Weak Axiom of Profit Maximization (WAPM) formulated by Varian [ (1984) The Non-parametric approach to production analysis. Econometrica 52:3 (May) 579–597] based on shadow prices rather than actual prices. At these shadow prices, the shadow profit of a firm is zero. The maximum shadow profit that could have been attained at some other input–output bundle is shown to be a measure of the inefficiency of the firm. Because the benchmark input–output bundle is always an observed bundle from the data, it can be determined without having to solve any elaborate programming problem. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • Subhash Ray, 2007. "Shadow profit maximization and a measure of overall inefficiency," Journal of Productivity Analysis, Springer, vol. 27(3), pages 231-236, June.
    • Handle: RePEc:kap:jproda:v:27:y:2007:i:3:p:231-236
    DOI: 10.1007/s11123-007-0036-8
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    References listed on IDEAS

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    1. Walter Briec & Hervé Leleu, 2003. "Dual Representations of Non-Parametric Technologies and Measurement of Technical Efficiency," Journal of Productivity Analysis, Springer, vol. 20(1), pages 71-96, July.
    2. Frances Frei & Patrick Harker, 1999. "Projections Onto Efficient Frontiers: Theoretical and Computational Extensions to DEA," Journal of Productivity Analysis, Springer, vol. 11(3), pages 275-300, June.
    3. Ray, Subhash C. & Jeon, Yongil, 2008. "Reputation and efficiency: A non-parametric assessment of America's top-rated MBA programs," European Journal of Operational Research, Elsevier, vol. 189(1), pages 245-268, August.
    4. Fare, Rolf & Knox Lovell, C. A., 1978. "Measuring the technical efficiency of production," Journal of Economic Theory, Elsevier, vol. 19(1), pages 150-162, October.
    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.
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    Citations

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    Cited by:

    1. Nurhan Davutyan & Canan Yildirim, 2013. "Competitiveness in Turkish Banking: 2002-2011," Working Papers 774, Economic Research Forum, revised Sep 2013.
    2. Aparicio, Juan & Monge, Juan F., 2022. "The generalized range adjusted measure in data envelopment analysis: Properties, computational aspects and duality," European Journal of Operational Research, Elsevier, vol. 302(2), pages 621-632.
    3. Leleu, Hervé, 2013. "Inner and outer approximations of technology: A shadow profit approach," Omega, Elsevier, vol. 41(5), pages 868-871.
    4. Aparicio, Juan & Ortiz, Lidia & Pastor, Jesus T., 2017. "Measuring and decomposing profit inefficiency through the Slacks-Based Measure," European Journal of Operational Research, Elsevier, vol. 260(2), pages 650-654.
    5. Aparicio, Juan & Pastor, Jesus T. & Ray, Subhash C., 2013. "An overall measure of technical inefficiency at the firm and at the industry level: The ‘lost profit on outlay’," European Journal of Operational Research, Elsevier, vol. 226(1), pages 154-162.
    6. Jose Zofio & Jesus Pastor & Juan Aparicio, 2013. "The directional profit efficiency measure: on why profit inefficiency is either technical or allocative," Journal of Productivity Analysis, Springer, vol. 40(3), pages 257-266, December.
    7. W D A Bryant, 2009. "General Equilibrium:Theory and Evidence," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6875, December.
    8. Paul Oslington, 2012. "General Equilibrium: Theory and Evidence," The Economic Record, The Economic Society of Australia, vol. 88(282), pages 446-448, September.
    9. Camanho, Ana Santos & Silva, Maria Conceicao & Piran, Fabio Sartori & Lacerda, Daniel Pacheco, 2024. "A literature review of economic efficiency assessments using Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 315(1), pages 1-18.
    10. Kuosmanen, Timo & Kortelainen, Mika & Sipiläinen, Timo & Cherchye, Laurens, 2010. "Firm and industry level profit efficiency analysis using absolute and uniform shadow prices," European Journal of Operational Research, Elsevier, vol. 202(2), pages 584-594, April.
    11. Aparicio, Juan & Borras, Fernando & Pastor, Jesus T. & Vidal, Fernando, 2015. "Measuring and decomposing firm׳s revenue and cost efficiency: The Russell measures revisited," International Journal of Production Economics, Elsevier, vol. 165(C), pages 19-28.
    12. Jesus Pastor & C. Lovell & Juan Aparicio, 2012. "Families of linear efficiency programs based on Debreu’s loss function," Journal of Productivity Analysis, Springer, vol. 38(2), pages 109-120, October.
    13. Subhash C. Ray, 2018. "Data Envelopment Analysis with Alternative Returns to Scale," Working papers 2018-20, University of Connecticut, Department of Economics.
    14. Ray, Subhash C, 2019. "The transformation function, technical efficiency, and the CCR ratio," European Journal of Operational Research, Elsevier, vol. 278(2), pages 422-429.

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    More about this item

    Keywords

    Shadow prices; Weak Axiom of Profit Maximization; Data envelopment analysis; C61; D20;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D20 - Microeconomics - - Production and Organizations - - - General

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