IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v62y2011i7d10.1057_jors.2010.108.html
   My bibliography  Save this article

Negative data in DEA: a simple proportional distance function approach

Author

Listed:
  • K Kerstens

    (IESEG School of Management)

  • I Van de Woestyne

    (Hogeschool Universiteit Brussel)

Abstract

The need to adapt Data Envelopment Analysis (DEA) and other frontier models in the context of negative data has been a rather neglected issue in the literature. A recent article in this journal proposed a variation on the directional distance function, a very general distance function that is dual to the profit function, to accommodate the occurrence of negative data. In this contribution, we define and recommend a generalised Farrell proportional distance function that can do the same job and that maintains a proportional interpretation under mild conditions.

Suggested Citation

  • K Kerstens & I Van de Woestyne, 2011. "Negative data in DEA: a simple proportional distance function approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1413-1419, July.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:7:d:10.1057_jors.2010.108
    DOI: 10.1057/jors.2010.108
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/jors.2010.108
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/jors.2010.108?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    2. Briec, Walter & Kerstens, Kristiaan, 2010. "Portfolio selection in multidimensional general and partial moment space," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 636-656, April.
    3. Andrew Worthington, 2001. "An Empirical Survey of Frontier Efficiency Measurement Techniques in Education," Education Economics, Taylor & Francis Journals, vol. 9(3), pages 245-268.
    4. Forsund, Finn R. & Sarafoglou, Nikias, 2005. "The tale of two research communities: The diffusion of research on productive efficiency," International Journal of Production Economics, Elsevier, vol. 98(1), pages 17-40, October.
    5. Murthi, B. P. S. & Choi, Yoon K. & Desai, Preyas, 1997. "Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach," European Journal of Operational Research, Elsevier, vol. 98(2), pages 408-418, April.
    6. Walter Briec & K. Kerstens, 2009. "Infeasibilities and directional distance functions: with application to the determinateness of the luenberger productivity indicator," Post-Print hal-00372560, HAL.
    7. W. Briec & K. Kerstens, 2009. "Infeasibility and Directional Distance Functions with Application to the Determinateness of the Luenberger Productivity Indicator," Journal of Optimization Theory and Applications, Springer, vol. 141(1), pages 55-73, April.
    8. Emrouznejad, Ali & Parker, Barnett R. & Tavares, Gabriel, 2008. "Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 151-157, September.
    9. E H Feroz & S Kim & R L Raab, 2003. "Financial statement analysis: A data envelopment analysis approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(1), pages 48-58, January.
    10. M C A Silva Portela & E Thanassoulis & G Simpson, 2004. "Negative data in DEA: a directional distance approach applied to bank branches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1111-1121, October.
    11. R. Robert Russell & William Schworm, 2009. "Axiomatic Foundations of Inefficiency Measurement on Space," Discussion Papers 2009-07, School of Economics, The University of New South Wales.
    12. Bruno De Borger & Kristiaan Kerstens & Álvaro Costa, 2002. "Public transit performance: What does one learn from frontier studies?," Transport Reviews, Taylor & Francis Journals, vol. 22(1), pages 1-38, January.
    13. W. Briec, 1997. "A Graph-Type Extension of Farrell Technical Efficiency Measure," Journal of Productivity Analysis, Springer, vol. 8(1), pages 95-110, March.
    14. Wade D. Cook & Joe Zhu, 2007. "Data Irregularities And Structural Complexities In Dea," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 1-11, Springer.
    15. 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.
    16. Smith, P, 1990. "Data envelopment analysis applied to financial statements," Omega, Elsevier, vol. 18(2), pages 131-138.
    17. Jean-Paul Chavas & Kwansoo Kim, 2007. "Measurement and Sources of Economies of Scope: A Primal Approach," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 163(3), pages 411-427, September.
    18. Yasar A. Ozcan, 2008. "Health Care Benchmarking and Performance Evaluation," International Series in Operations Research and Management Science, Springer, number 978-0-387-75448-2, April.
    19. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    20. Robert G. Chambers, 2002. "Exact nonradial input, output, and productivity measurement," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 20(4), pages 751-765.
    21. Jesús T. Pastor & José L. Ruiz, 2007. "Variables With Negative Values In Dea," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 63-84, Springer.
    22. DE BORGER, Bruno & KERSTENS, Kristiaan & COSTA, Álvaro, "undated". "Public transit performance: What do we learn from frontier studies?," Working Papers 2000019, University of Antwerp, Faculty of Business and Economics.
    23. 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.
    24. Patrick T. Harker & Stavros A. Zenios, 1998. "What Drives the Performance of Financial Institutions?," Center for Financial Institutions Working Papers 98-21, Wharton School Center for Financial Institutions, University of Pennsylvania.
    25. J A Sharp & W Meng & W Liu, 2007. "A modified slacks-based measure model for data envelopment analysis with ‘natural’ negative outputs and inputs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1672-1677, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Barra, Cristian & Zotti, Roberto, 2014. "Handling negative data using Data Envelopment Analysis: a directional distance approach applied to higher education," MPRA Paper 55570, University Library of Munich, Germany.
    2. Asmild, Mette & Pastor, Jesús T., 2010. "Slack free MEA and RDM with comprehensive efficiency measures," Omega, Elsevier, vol. 38(6), pages 475-483, December.
    3. Zotti, Roberto & Barra, Cristian, 2014. "Human capital development, knowledge spillovers and local growth: Is there a quality effect of university efficiency?," MPRA Paper 60065, University Library of Munich, Germany.
    4. Kao, Chiang, 2020. "Measuring efficiency in a general production possibility set allowing for negative data," European Journal of Operational Research, Elsevier, vol. 282(3), pages 980-988.
    5. Mehdiloozad, Mahmood & Zhu, Joe & Sahoo, Biresh K., 2018. "Identification of congestion in data envelopment analysis under the occurrence of multiple projections: A reliable method capable of dealing with negative data," European Journal of Operational Research, Elsevier, vol. 265(2), pages 644-654.
    6. Wai‐Peng Wong & Qiang Deng & Ming-Lang Tseng & Loo‐Hay Lee & Chee‐Wooi Hooy, 2014. "A Stochastic Setting To Bank Financial Performance For Refining Efficiency Estimates," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(4), pages 225-245, October.
    7. Jradi, Samah & Bouzdine Chameeva, Tatiana & Aparicio, Juan, 2019. "The measurement of revenue inefficiency over time: An additive perspective," Omega, Elsevier, vol. 83(C), pages 167-180.
    8. Ruiyue Lin & Zhiping Chen & Qianhui Hu & Zongxin Li, 2017. "Dynamic network DEA approach with diversification to multi-period performance evaluation of funds," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 821-860, July.
    9. Youchao Tan & Udaya Shetty & Ali Diabat & T. Pakkala, 2015. "Aggregate directional distance formulation of DEA with integer variables," Annals of Operations Research, Springer, vol. 235(1), pages 741-756, December.
    10. Juan Aparicio & Fernando Borras & Lidia Ortiz & Jesus T. Pastor & Fernando Vidal, 2019. "Luenberger-type indicators based on the weighted additive distance function," Annals of Operations Research, Springer, vol. 278(1), pages 195-213, July.
    11. Briec, Walter & Dumas, Audrey & Kerstens, Kristiaan & Stenger, Agathe, 2022. "Generalised commensurability properties of efficiency measures: Implications for productivity indicators," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1481-1492.
    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. Rafael Benítez & Vicente Coll-Serrano & Vicente J. Bolós, 2021. "deaR-Shiny: An Interactive Web App for Data Envelopment Analysis," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    14. Daraio, Cinzia & Kerstens, Kristiaan & Nepomuceno, Thyago & Sickles, Robin C., 2019. "Empirical Surveys of Frontier Applications: A Meta-Review," Working Papers 19-005, Rice University, Department of Economics.
    15. William Cooper & Jesús Pastor & Fernando Borras & Juan Aparicio & Diego Pastor, 2011. "BAM: a bounded adjusted measure of efficiency for use with bounded additive models," Journal of Productivity Analysis, Springer, vol. 35(2), pages 85-94, April.
    16. Halická, Margaréta & Trnovská, Mária & Černý, Aleš, 2024. "A unified approach to radial, hyperbolic, and directional efficiency measurement in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 312(1), pages 298-314.
    17. Mehdiloo, Mahmood & Podinovski, Victor V., 2021. "Strong, weak and Farrell efficient frontiers of technologies satisfying different production assumptions," European Journal of Operational Research, Elsevier, vol. 294(1), pages 295-311.
    18. Ravelojaona, Paola, 2019. "On constant elasticity of substitution – Constant elasticity of transformation Directional Distance Functions," European Journal of Operational Research, Elsevier, vol. 272(2), pages 780-791.
    19. Tarnaud, Albane Christine & Leleu, Hervé, 2018. "Portfolio analysis with DEA: Prior to choosing a model," Omega, Elsevier, vol. 75(C), pages 57-76.
    20. Juan Aparicio & Magdalena Kapelko & Bernhard Mahlberg & Jose L. Sainz-Pardo, 2017. "Measuring input-specific productivity change based on the principle of least action," Journal of Productivity Analysis, Springer, vol. 47(1), pages 17-31, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorsoc:v:62:y:2011:i:7:d:10.1057_jors.2010.108. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.