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The Directional Profit Efficiency Measure: On Why Profit Inefficiency is either Technical or Allocative

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  • Zofío, José Luis

    () (Departamento de Análisis Económico (Teoría e Historia Económica). Universidad Autónoma de Madrid.)

  • Pastor, Jesús

    (Center of Operations Research, Universidad Miguel Hernández, Elche, Spain)

  • Aparicio, Juan

    (Center of Operations Research, Universidad Miguel Hernández, Elche, Spain)

Abstract

The directional distance function has been introduced in the efficiency literature with the intention of relaxing the fixed orientations represented by its classical input and output counterparts. However, the criteria underlying the choice of its associated directional vector are numerous. When market prices are observed and firms have a profit maximizing behavior, it seems natural to choose as directional vector that projecting inefficient firms towards profit maximizing benchmarks. Based on that choice of directional vector, we introduce the profit efficiency measure and show that, in this general setting, profit inefficiency can be categorized as either technical -for firms situating in the interior of the technology- or allocative -for firms lying on the frontier. We implement and illustrate the analytical model by way of Data Envelopment Analysis techniques, where the profit maximizing benchmark may not be unique, and introduce the necessary optimizing program for profit inefficiency measurement.

Suggested Citation

  • Zofío, José Luis & Pastor, Jesús & Aparicio, Juan, 2010. "The Directional Profit Efficiency Measure: On Why Profit Inefficiency is either Technical or Allocative," Working Papers in Economic Theory 2010/09, Universidad Autónoma de Madrid (Spain), Department of Economic Analysis (Economic Theory and Economic History).
  • Handle: RePEc:uam:wpaper:201009
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Pedro Macedo & Elvira Silva, 2017. "Sensitivity of directional technical inefficiency measures to the choice of the direction vector: a simulation study," Economics Bulletin, AccessEcon, vol. 37(1), pages 52-62.
    2. repec:kap:jproda:v:48:y:2017:i:2:d:10.1007_s11123-017-0512-8 is not listed on IDEAS
    3. Lee, Chia-Yen, 2016. "Nash-profit efficiency: A measure of changes in market structures," European Journal of Operational Research, Elsevier, vol. 255(2), pages 659-663.
    4. repec:spr:empeco:v:54:y:2018:i:1:d:10.1007_s00181-017-1233-6 is not listed on IDEAS
    5. Aparicio, Juan & Pastor, Jesus T. & Zofio, Jose L., 2015. "How to properly decompose economic efficiency using technical and allocative criteria with non-homothetic DEA technologies," European Journal of Operational Research, Elsevier, vol. 240(3), pages 882-891.
    6. Cinzia Daraio & Léopold Simar, 2016. "Efficiency and benchmarking with directional distances: a data-driven approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(7), pages 928-944, July.
    7. Pastor, Jesus T. & Zofio, Jose L., 2017. "Can Farrell's allocative efficiency be generalized by the directional distance function approach?Author-Name: Aparicio, Juan," European Journal of Operational Research, Elsevier, vol. 257(1), pages 345-351.
    8. repec:eee:ejores:v:262:y:2017:i:1:p:361-369 is not listed on IDEAS
    9. Ke Wang & Yujiao Xian & Chia-Yen Lee & Yi-Ming Wei & Zhimin Huang, 2017. "On selecting directions for directional distance functions in a non-parametric framework: A review," CEEP-BIT Working Papers 99, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    10. Álvarez, Inmaculada & Barbero, Javier & Zofío, Jose Luis, 2016. "A Data Envelopment Analysis Toolbox for MATLAB," Working Papers in Economic Theory 2016/03, Universidad Autónoma de Madrid (Spain), Department of Economic Analysis (Economic Theory and Economic History).
    11. Mircea Epure, 2016. "Benchmarking for routines and organizational knowledge: a managerial accounting approach with performance feedback," Journal of Productivity Analysis, Springer, vol. 46(1), pages 87-107, August.
    12. Lee, Chia-Yen, 2014. "Meta-data envelopment analysis: Finding a direction towards marginal profit maximization," European Journal of Operational Research, Elsevier, vol. 237(1), pages 207-216.
    13. repec:eee:jomega:v:72:y:2017:i:c:p:1-14 is not listed on IDEAS
    14. repec:eee:ejores:v:262:y:2017:i:2:p:792-801 is not listed on IDEAS
    15. Juan Aparicio & José L. Zofío, 2017. "Revisiting the decomposition of cost efficiency for non-homothetic technologies: a directional distance function approach," Journal of Productivity Analysis, Springer, vol. 48(2), pages 133-146, December.
    16. repec:eee:ejores:v:266:y:2018:i:3:p:1013-1024 is not listed on IDEAS

    More about this item

    Keywords

    Directional Distance Function; Profit Efficiency; Technical Efficiency; Allocative Efficiency; Data Envelopment Analysis.;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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