IDEAS home Printed from https://ideas.repec.org/a/kap/jproda/v9y1998i3p187-204.html
   My bibliography  Save this article

The Effect of Sample Size on the Mean Efficiency in DEA with an Application to Electricity Distribution in Australia, Sweden and New Zealand

Author

Listed:
  • Yun Zhang
  • Robert Bartels

Abstract

This study examines the effect of sample size on the mean productive efficiency of firms when the efficiency is evaluated using the non-parametric approach of Data Envelopment Analysis. By employing Monte Carlo simulation, we show how the mean efficiency is related to the sample size. The paper discusses the implications for international comparisons. As an application, we investigate the efficiency of the electricity distribution industries in Australia, Sweden and New Zealand. Copyright Kluwer Academic Publishers 1998

Suggested Citation

  • Yun Zhang & Robert Bartels, 1998. "The Effect of Sample Size on the Mean Efficiency in DEA with an Application to Electricity Distribution in Australia, Sweden and New Zealand," Journal of Productivity Analysis, Springer, vol. 9(3), pages 187-204, March.
    • Handle: RePEc:kap:jproda:v:9:y:1998:i:3:p:187-204
    DOI: 10.1023/A:1018395303580
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1018395303580
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1023/A:1018395303580?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Gong, Byeong-Ho & Sickles, Robin C., 1992. "Finite sample evidence on the performance of stochastic frontiers and data envelopment analysis using panel data," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 259-284.
    2. 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.
    3. Banker, Rajiv D. & Gadh, Vandana M. & Gorr, Wilpen L., 1993. "A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 67(3), pages 332-343, June.
    4. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
    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. Don U.A. Galagedera, 2004. "A Survey On Investment Performance Appraisal Methods With Special Reference To Data Envelopment Analysis," Finance 0406013, University Library of Munich, Germany.
    2. Ahn, Heinz & Clermont, Marcel & Langner, Julia, 2023. "Comparative performance analysis of frontier-based efficiency measurement methods – A Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 307(1), pages 294-312.
    3. John Ruggiero, 2004. "Data envelopment analysis with stochastic data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(9), pages 1008-1012, September.
    4. Julia Schaefer & Marcel Clermont, 2018. "Stochastic non-smooth envelopment of data for multi-dimensional output," Journal of Productivity Analysis, Springer, vol. 50(3), pages 139-154, December.
    5. Resti, Andrea, 2000. "Efficiency measurement for multi-product industries: A comparison of classic and recent techniques based on simulated data," European Journal of Operational Research, Elsevier, vol. 121(3), pages 559-578, March.
    6. Mark Andor & Frederik Hesse, 2014. "The StoNED age: the departure into a new era of efficiency analysis? A monte carlo comparison of StoNED and the “oldies” (SFA and DEA)," Journal of Productivity Analysis, Springer, vol. 41(1), pages 85-109, February.
    7. John Ruggiero & Donald F. Vitaliano, 1999. "Assessing The Efficiency Of Public Schools Using Data Envelopment Analysis And Frontier Regression," Contemporary Economic Policy, Western Economic Association International, vol. 17(3), pages 321-331, July.
    8. Banker, Rajiv D. & Chang, Hsihui, 1995. "A simulation study of hypothesis tests for differences in efficiencies," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 37-54, April.
    9. Li, Susan X., 1998. "Stochastic models and variable returns to scales in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 104(3), pages 532-548, February.
    10. Oleg Badunenko & Daniel J. Henderson & Subal C. Kumbhakar, 2012. "When, where and how to perform efficiency estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(4), pages 863-892, October.
    11. Krüger, Jens J., 2012. "A Monte Carlo study of old and new frontier methods for efficiency measurement," European Journal of Operational Research, Elsevier, vol. 222(1), pages 137-148.
    12. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    13. Sethi, Amarjit Singh, 2016. "Sources of Growth in India: Evidence from Punjab and Haryana," Journal of Regional Development and Planning, Rajarshi Majumder, vol. 5(1), pages 15-34.
    14. Yu, Chunyan, 1998. "The effects of exogenous variables in efficiency measurement--A monte carlo study," European Journal of Operational Research, Elsevier, vol. 105(3), pages 569-580, March.
    15. Ruggiero, John, 2006. "Measurement error, education production and data envelopment analysis," Economics of Education Review, Elsevier, vol. 25(3), pages 327-333, June.
    16. Olesen, Ole B. & Petersen, Niels Christian, 2016. "Stochastic Data Envelopment Analysis—A review," European Journal of Operational Research, Elsevier, vol. 251(1), pages 2-21.
    17. Bifulco, Robert & Bretschneider, Stuart, 2001. "Estimating school efficiency: A comparison of methods using simulated data," Economics of Education Review, Elsevier, vol. 20(5), pages 417-429, October.
    18. Holland, D. S. & Lee, S. T., 2002. "Impacts of random noise and specification on estimates of capacity derived from data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 137(1), pages 10-21, February.
    19. Luo, Xueming & Donthu, Naveen, 2005. "Assessing advertising media spending inefficiencies in generating sales," Journal of Business Research, Elsevier, vol. 58(1), pages 28-36, January.
    20. Perelman, Sergio & Santín, Daniel, 2009. "How to generate regularly behaved production data? A Monte Carlo experimentation on DEA scale efficiency measurement," European Journal of Operational Research, Elsevier, vol. 199(1), pages 303-310, November.

    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:kap:jproda:v:9:y:1998:i:3:p:187-204. 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.

    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.springer.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.