IDEAS home Printed from
   My bibliography  Save this article

Measuring Public Owned University Departments' Efficiency: A Bootstrapped DEA Approach


  • George E. Halkos
  • Nickolaos G. Tzeremes
  • Stavros A. Kourtzidis


This article uses Data Envelopment Analysis (DEA) in order to determine the performance levels of 16 departments of a public owned university. Particularly, the constant returns to scale (CRS) and variable returns to scale (VRS) models have been applied alongside with bootstrap techniques in order to determine accurate performance estimates. The study illustrates how the recent developments in efficiency analysis and statistical inference can be applied when evaluating institutional performance issues. The results reveal the existence of misallocation of resources or/and inefficient application of departments’ policy development.

Suggested Citation

  • George E. Halkos & Nickolaos G. Tzeremes & Stavros A. Kourtzidis, 2012. "Measuring Public Owned University Departments' Efficiency: A Bootstrapped DEA Approach," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 55(2), pages 1-24.
  • Handle: RePEc:eei:journl:v:55:y:2012:i:2:p:1-24

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

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

    References listed on IDEAS

    1. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    2. Izadi, Hooshang & Johnes, Geraint & Oskrochi, Reza & Crouchley, Robert, 2002. "Stochastic frontier estimation of a CES cost function: the case of higher education in Britain," Economics of Education Review, Elsevier, vol. 21(1), pages 63-71, February.
    3. Jill Johnes, 2006. "Measuring Efficiency: A Comparison of Multilevel Modelling and Data Envelopment Analysis in the Context of Higher Education," Bulletin of Economic Research, Wiley Blackwell, vol. 58(2), pages 75-104, April.
    4. George Halkos & Nickolaos Tzeremes, 2010. "The effect of foreign ownership on SMEs performance: An efficiency analysis perspective," Journal of Productivity Analysis, Springer, vol. 34(2), pages 167-180, October.
    5. Abbott, M. & Doucouliagos, C., 2003. "The efficiency of Australian universities: a data envelopment analysis," Economics of Education Review, Elsevier, vol. 22(1), pages 89-97, February.
    6. Cohn, Elchanan & Rhine, Sherrie L W & Santos, Maria C, 1989. "Institutions of Higher Education as Multi-product Firms: Economies of Scale and Scope," The Review of Economics and Statistics, MIT Press, vol. 71(2), pages 284-290, May.
    7. Beasley, J. E., 1990. "Comparing university departments," Omega, Elsevier, vol. 18(2), pages 171-183.
    8. Gary Madden & Scott Savage & Steven Kemp, 1997. "Measuring Public Sector Efficiency: A Study of Economics Departments at Australian Universities," Education Economics, Taylor & Francis Journals, vol. 5(2), pages 153-168.
    9. Tommaso Agasisti & Geraint Johnes, 2010. "Heterogeneity and the evaluation of efficiency: the case of Italian universities," Applied Economics, Taylor & Francis Journals, vol. 42(11), pages 1365-1375.
    10. Johnes, Jill, 2006. "Data envelopment analysis and its application to the measurement of efficiency in higher education," Economics of Education Review, Elsevier, vol. 25(3), pages 273-288, June.
    11. Léopold Simar & Valentin Zelenyuk, 2007. "Statistical inference for aggregates of Farrell-type efficiencies," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(7), pages 1367-1394.
    12. Ahn, Taesik & Charnes, Abraham & Cooper, William W., 1988. "Some statistical and DEA evaluations of relative efficiencies of public and private institutions of higher learning," Socio-Economic Planning Sciences, Elsevier, vol. 22(6), pages 259-269.
    13. Valentin Zelenyuk & Vitaliy Zheka, 2006. "Corporate Governance and Firm’s Efficiency: The Case of a Transitional Country, Ukraine," Journal of Productivity Analysis, Springer, vol. 25(1), pages 143-157, April.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. Barra, Cristian & Lagravinese, Raffaele & Zotti, Roberto, 2015. "Explaining (in)efficiency in higher education: a comparison of parametric and non-parametric analyses to rank universities," MPRA Paper 67119, University Library of Munich, Germany.
    2. Agasisti, Tommaso & Barra, Cristian & Zotti, Roberto, 2016. "Evaluating the efficiency of Italian public universities (2008–2011) in presence of (unobserved) heterogeneity," Socio-Economic Planning Sciences, Elsevier, vol. 55(C), pages 47-58.
    3. Mehdi Rhaiem, 2017. "Measurement and determinants of academic research efficiency: a systematic review of the evidence," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 581-615, February.
    4. Tommaso Agasisti & Cristian Barra & Roberto Zotti, 2017. "Research, knowledge transfer and innovation: the effect of Italian universities’ efficiency on the local economic development 2006-2012," Working papers 60, Società Italiana di Economia Pubblica.
    5. Cristian Barra & Roberto Zotti, 2016. "Measuring Efficiency in Higher Education: An Empirical Study Using a Bootstrapped Data Envelopment Analysis," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(1), pages 11-33, February.

    More about this item


    Departments’ efficiency; Data Envelopment Analysis; bootstrap techniques; Kernel density estimation.;

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • I20 - Health, Education, and Welfare - - Education - - - General
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions


    Access and download statistics


    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:eei:journl:v:55:y:2012:i:2:p:1-24. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Julia van Hove). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.