IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/54101.html
   My bibliography  Save this paper

Estimating Economic Efficiencies of Public Sector Organisations with Stochastic Frontier Analysis: Evidence from Turkish Higher Education

Author

Listed:
  • Erkoc, Taptuk Emre

Abstract

This paper investigates 53 public HEIs in Turkey between 2005 and 2010 including 5 full academic terms to estimate both their cost frontier and inefficiencies. The initial findings of six different models imply that Turkish universities perform quite well concerning their overall efficiency values albeit with variations among them. Besides, within this five-year time span, Turkish universities have not shown any improvement in their efficiencies based on Battese and Coelli's (1992) time variant model. In addition to that, the determinants of inefficiencies in Turkish HEIs are dependent upon certain variables. The size of HEIs is seen to be the most influential factor behind inefficiencies referring to the fact that small size universities are expected to experience relatively higher efficiency results. Subsequently, the impact of load factor is as important as the size effect. The negative coefficient implies that, universities with higher load factor demonstrate better efficiency performances. Moreover, age of the university, the percentage of foreign students, percentage of full-time faculty and having medical school are the other variables reducing efficiency in HEIs based on the only one model. Percentage of professors does not have any influence on the inefficiencies according to the both two models.

Suggested Citation

  • Erkoc, Taptuk Emre, 2013. "Estimating Economic Efficiencies of Public Sector Organisations with Stochastic Frontier Analysis: Evidence from Turkish Higher Education," MPRA Paper 54101, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:54101
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/54101/1/MPRA_paper_54101.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Johnes, Geraint & Johnes, Jill, 2009. "Higher education institutions' costs and efficiency: Taking the decomposition a further step," Economics of Education Review, Elsevier, vol. 28(1), pages 107-113, February.
    2. Mensah, Yaw M. & Werner, Robert, 2003. "Cost efficiency and financial flexibility in institutions of higher education," Journal of Accounting and Public Policy, Elsevier, vol. 22(4), pages 293-323.
    3. Karim, M.Z.A. & Jhantasana, Ch., 2005. "Efficiency and Profitability in Thailand’s Life Insurance Industry: A Cost Frontier Function and Hausman test, 1997-2002," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(4), pages 19-36.
    4. Mehdi Farsi & Massimo Filippini & Michael Kuenzle, 2005. "Unobserved heterogeneity in stochastic cost frontier models: an application to Swiss nursing homes," Applied Economics, Taylor & Francis Journals, vol. 37(18), pages 2127-2141.
    5. Philip Stevens, 2001. "The determinants of economic efficiency in English and Welsh universities," National Institute of Economic and Social Research (NIESR) Discussion Papers 185, National Institute of Economic and Social Research.
    6. Daghbashyan, Zara, 2011. "The Economic Efficiency of Swedish Higher Education Institutions," Working Paper Series in Economics and Institutions of Innovation 245, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies, revised 17 Dec 2012.
    7. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    8. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    9. Kopp, Raymond J. & Diewert, W. Erwin, 1982. "The decomposition of frontier cost function deviations into measures of technical and allocative efficiency," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 319-331, August.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Shukhrat Kholmuminov & Robert E Wright, 2017. "Cost efficiency analysis of public higher education institutions in Uzbekistan," Working Papers 1704, University of Strathclyde Business School, Department of Economics.

    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. Gralka, Sabine, 2018. "Stochastic frontier analysis in higher education: A systematic review," CEPIE Working Papers 05/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    2. T Agasisti & G Johnes, 2009. "Cost Structure, Efficiency and Heterogeneity in US Higher Education: An Empirical Analysis," Working Papers 599308, Lancaster University Management School, Economics Department.
    3. Vanesa D’Elia & Gustavo Ferro, 2019. "Empirical Efficiency Measurement in Higher Education: An Overview," CEMA Working Papers: Serie Documentos de Trabajo. 708, Universidad del CEMA.
    4. Massimo Filippini & Martin Koller, 2012. "Cost Efficiency Measurement in Postal Delivery Networks," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 1206, USI Università della Svizzera italiana.
    5. Bolli, Thomas & Olivares, Maria & Bonaccorsi, Andrea & Daraio, Cinzia & Aracil, Adela Garcia & Lepori, Benedetto, 2016. "The differential effects of competitive funding on the production frontier and the efficiency of universities," Economics of Education Review, Elsevier, vol. 52(C), pages 91-104.
    6. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    7. Raushan Bokusheva & Lukáš Čechura & Subal C. Kumbhakar, 2023. "Estimating persistent and transient technical efficiency and their determinants in the presence of heterogeneity and endogeneity," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 450-472, June.
    8. Mehdi Farsi & Aurelio Fetz & Massimo Filippini, 2007. "Benchmarking and Regulation in the Electricity Distribution Sector," CEPE Working paper series 07-54, CEPE Center for Energy Policy and Economics, ETH Zurich.
    9. Tung Liu, 2020. "Measuring Technical, Allocative inefficiency, and Cost Inefficiency by Applying Duality Theory," Working Papers 202001, Ball State University, Department of Economics, revised Jun 2020.
    10. Sabrina Auci & Laura Castellucci & Manuela Coromaldi, 2021. "How does public spending affect technical efficiency? Some evidence from 15 European countries," Bulletin of Economic Research, Wiley Blackwell, vol. 73(1), pages 108-130, January.
    11. Cazals Catherine & Dudley Paul & Florens Jean-Pierre & Jones Michael, 2011. "The Effect of Unobserved Heterogeneity in Stochastic Frontier Estimation: Comparison of Cross Section and Panel with Simulated Data for the Postal Sector," Review of Network Economics, De Gruyter, vol. 10(3), pages 1-22, September.
    12. Castiglione, Concetta & Infante, Davide & Zieba, Marta, 2023. "Public support for performing arts. Efficiency and productivity gains in eleven European countries," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    13. Shukhrat Kholmuminov & Robert E Wright, 2017. "Cost efficiency analysis of public higher education institutions in Uzbekistan," Working Papers 1704, University of Strathclyde Business School, Department of Economics.
    14. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    15. Geraint Johnes, 2015. "Evaluating the efficiency of public services," IZA World of Labor, Institute of Labor Economics (IZA), pages 196-196, October.
    16. Boris E. Bravo‐Ureta & Víctor H. Moreira & Javier L. Troncoso & Alan Wall, 2020. "Plot‐level technical efficiency accounting for farm‐level effects: Evidence from Chilean wine grape producers," Agricultural Economics, International Association of Agricultural Economists, vol. 51(6), pages 811-824, November.
    17. Massimo Filippini & Elisa Tosetti, 2014. "Stochastic Frontier Models for Long Panel Data Sets: Measurement of the Underlying Energy Efficiency for the OECD Countries," CER-ETH Economics working paper series 14/198, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    18. Manuel Llorca & José Baños & José Somoza & Pelayo Arbués, 2017. "A Stochastic Frontier Analysis Approach for Estimating Energy Demand and Efficiency in the Transport Sector of Latin America and the Caribbean," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    19. Mehdi Farsi & Massimo Filippini & William Greene, 2005. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," Journal of Regulatory Economics, Springer, vol. 28(1), pages 69-90, July.
    20. Llorca, Manuel & Baños, José & Somoza, José & Arbués, Pelayo, 2014. "A latent class approach for estimating energy demands and efficiency in transport: An application to Latin America and the Caribbean," Efficiency Series Papers 2014/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).

    More about this item

    Keywords

    Panel Data Models; Stochastic Frontier Analysis; Cost efficiency; Universities;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions

    Statistics

    Access and download statistics

    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:pra:mprapa:54101. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.