IDEAS home Printed from https://ideas.repec.org/a/ids/ijores/v9y2010i2p188-204.html
   My bibliography  Save this article

Incorporating heterogeneity in non-parametric models: a methodological comparison

Author

Listed:
  • Kristof De Witte
  • Rui Cunha Marques

Abstract

The operational environment can heavily influence the efficiency scores of the evaluated observations. If heterogeneity among entities is neglected, the efficiency evaluation is strongly biased. In this paper, we discuss five methodologies to incorporate heterogeneity in non-parametric frontier models which are robust for outlying observations. In particular, we examine the frontier separation approach, the all-in-one model, the two-stage model, the multi-stage approach and the conditional efficiency measures. We discuss their appropriateness on a simulated and a real-world drinking water data set. Although, the outcomes are closely related on average, the robust conditional efficiency procedure seems to be superior.

Suggested Citation

  • Kristof De Witte & Rui Cunha Marques, 2010. "Incorporating heterogeneity in non-parametric models: a methodological comparison," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 9(2), pages 188-204.
    • Handle: RePEc:ids:ijores:v:9:y:2010:i:2:p:188-204
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=35044
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mocholi-Arce, Manuel & Sala-Garrido, Ramon & Molinos-Senante, Maria & Maziotis, Alexandros, 2021. "Performance assessment of water companies: A metafrontier approach accounting for quality of service and group heterogeneities," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    2. Manuel Salas-Velasco, 2024. "Nonparametric efficiency measurement of undergraduate teaching by university size," Operational Research, Springer, vol. 24(1), pages 1-29, March.
    3. María Molinos-Senante & Alexandros Maziotis, 2019. "Cost Efficiency of English and Welsh Water Companies: a Meta-Stochastic Frontier Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3041-3055, July.
    4. Vilarinho, Hermilio & D’Inverno, Giovanna & Nóvoa, Henriqueta & Camanho, Ana S., 2023. "The measurement of asset management performance of water companies," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    5. Cordero, José Manuel & Alonso-Morán, Edurne & Nuño-Solinis, Roberto & Orueta, Juan F. & Arce, Regina Sauto, 2015. "Efficiency assessment of primary care providers: A conditional nonparametric approach," European Journal of Operational Research, Elsevier, vol. 240(1), pages 235-244.
    6. De Witte, Kristof & Geys, Benny, 2013. "Citizen coproduction and efficient public good provision: Theory and evidence from local public libraries," European Journal of Operational Research, Elsevier, vol. 224(3), pages 592-602.
    7. Vladimír Holý, 2022. "The impact of operating environment on efficiency of public libraries," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(1), pages 395-414, March.
    8. Fusco, Elisa & Vidoli, Francesco & Sahoo, Biresh K., 2018. "Spatial heterogeneity in composite indicator: A methodological proposal," Omega, Elsevier, vol. 77(C), pages 1-14.
    9. Sala-Garrido, Ramon & Mocholi-Arce, Manuel & Maziotis, Alexandros & Molinos-Senante, María, 2023. "The carbon and production performance of water utilities: Evidence from the English and Welsh water industry," Structural Change and Economic Dynamics, Elsevier, vol. 64(C), pages 292-300.
    10. De Clercq, Djavan & Wen, Zongguo & Caicedo, Luis & Cao, Xin & Fan, Fei & Xu, Ruifei, 2017. "Application of DEA and statistical inference to model the determinants of biomethane production efficiency: A case study in south China," Applied Energy, Elsevier, vol. 205(C), pages 1231-1243.
    11. Alda A. Henriques & Milton Fontes & Ana S. Camanho & Giovanna D’Inverno & Pedro Amorim & Jaime Gabriel Silva, 2022. "Performance evaluation of problematic samples: a robust nonparametric approach for wastewater treatment plants," Annals of Operations Research, Springer, vol. 315(1), pages 193-220, August.

    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:ids:ijores:v:9:y:2010:i:2:p:188-204. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=170 .

    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.