IDEAS home Printed from https://ideas.repec.org/p/cem/doctra/708.html
   My bibliography  Save this paper

Empirical Efficiency Measurement in Higher Education: An Overview

Author

Listed:
  • Vanesa D’Elia
  • Gustavo Ferro

Abstract

This paper reviews the most recent empirical literature that assesses efficiency in higher education. We analyze 76 studies ranging from 1997 to 2018 and classify them according to the methodologies applied and to the definitions used to describe the outputs, inputs, quality and the context variables. We find that 72 percent of the empirical studies use non-parametric approaches. The most recent studies use panel data. The degrees completed are the most frequently used output variable, and only 9 papers include quality variables. Moreover, while only few parametric papers take observed heterogeneity into account, more than 40 percent include environmental variables to address for observed heterogeneity. This review is useful for researchers interested in measuring efficiency, for policy makers and for other educational stakeholders.

Suggested Citation

  • 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.
  • Handle: RePEc:cem:doctra:708
    as

    Download full text from publisher

    File URL: https://ucema.edu.ar/publicaciones/download/documentos/708.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Tommaso Agasisti & Giuseppe Catalano & Paolo Landoni & Roberto Verganti, 2012. "Evaluating the performance of academic departments: an analysis of research-related output efficiency," Research Evaluation, Oxford University Press, vol. 21(1), pages 2-14, February.
    2. Johnes, Jill & Yu, Li, 2008. "Measuring the research performance of Chinese higher education institutions using data envelopment analysis," China Economic Review, Elsevier, vol. 19(4), pages 679-696, December.
    3. Johnes, Geraint & Johnes, Jill, 1993. "Measuring the Research Performance of UK Economics Departments: An Application of Data Envelopment Analysis," Oxford Economic Papers, Oxford University Press, vol. 45(2), pages 332-347, April.
    4. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    5. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    6. Kao, Chiang & Hung, Hsi-Tai, 2008. "Efficiency analysis of university departments: An empirical study," Omega, Elsevier, vol. 36(4), pages 653-664, August.
    7. Millot, Benoit, 2015. "International rankings: Universities vs. higher education systems," International Journal of Educational Development, Elsevier, vol. 40(C), pages 156-165.
    8. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    9. 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.
    10. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    11. Geraint Johnes & Jill Johnes (ed.), 2004. "International Handbook on the Economics of Education," Books, Edward Elgar Publishing, number 2847.
    12. 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.
    13. A. T. Flegg & D. O. Allen & K. Field & T. W. Thurlow, 2004. "Measuring the efficiency of British universities: a multi-period data envelopment analysis," Education Economics, Taylor & Francis Journals, vol. 12(3), pages 231-249.
    14. Geraint Johnes & Astrid Schwarzenberger, 2011. "Differences in cost structure and the evaluation of efficiency: the case of German universities," Education Economics, Taylor & Francis Journals, vol. 19(5), pages 487-499, January.
    15. Laureti, Tiziana & Secondi, Luca & Biggeri, Luigi, 2014. "Measuring the efficiency of teaching activities in Italian universities: An information theoretic approach," Economics of Education Review, Elsevier, vol. 42(C), pages 147-164.
    16. Gerhard Kempkes & Carsten Pohl, 2010. "The efficiency of German universities-some evidence from nonparametric and parametric methods," Applied Economics, Taylor & Francis Journals, vol. 42(16), pages 2063-2079.
    17. Daraio, Cinzia & Bonaccorsi, Andrea & Simar, Léopold, 2015. "Efficiency and economies of scale and specialization in European universities: A directional distance approach," Journal of Informetrics, Elsevier, vol. 9(3), pages 430-448.
    18. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    19. Calogero Guccio & Marco Ferdinando Martorana & Luisa Monaco, 2016. "Evaluating the impact of the Bologna Process on the efficiency convergence of Italian universities: a non-parametric frontier approach," Journal of Productivity Analysis, Springer, vol. 45(3), pages 275-298, June.
    20. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    21. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    22. Silvia Cantele & Andrea Guerrini & Bettina Campedelli, 2016. "Efficiency of Italian universities: the effect of controllable and non-controllable environmental and operational variables," International Journal of Public Policy, Inderscience Enterprises Ltd, vol. 12(3/4/5/6), pages 243-260.
    23. Wolszczak-Derlacz, Joanna, 2017. "An evaluation and explanation of (in)efficiency in higher education institutions in Europe and the U.S. with the application of two-stage semi-parametric DEA," Research Policy, Elsevier, vol. 46(9), pages 1595-1605.
    24. Lee, Boon L. & Worthington, Andrew C., 2016. "A network DEA quantity and quality-orientated production model: An application to Australian university research services," Omega, Elsevier, vol. 60(C), pages 26-33.
    25. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    26. A. T. Flegg & D. O. Allen, 2007. "Does Expansion Cause Congestion? The Case of the Older British Universities, 1994-2004," Education Economics, Taylor & Francis Journals, vol. 15(1), pages 75-102.
    27. Wolff, Edward N. & Baumol, William J. & Saini, Anne Noyes, 2014. "A comparative analysis of education costs and outcomes: The United States vs. other OECD countries," Economics of Education Review, Elsevier, vol. 39(C), pages 1-21.
    28. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    29. De Fraja, Gianni & Valbonesi, Paola, 2012. "The design of the university system," Journal of Public Economics, Elsevier, vol. 96(3), pages 317-330.
    30. 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.
    31. Jill Johnes, 2008. "Efficiency And Productivity Change In The English Higher Education Sector From 1996/97 To 2004/5," Manchester School, University of Manchester, vol. 76(6), pages 653-674, December.
    32. 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.
    33. Worthington, Andrew C. & Lee, Boon L., 2008. "Efficiency, technology and productivity change in Australian universities, 1998-2003," Economics of Education Review, Elsevier, vol. 27(3), pages 285-298, June.
    34. G. Thomas Sav, 2012. "Managing Operating Efficiencies of Publicly Owned Universities: American University Stochastic Frontier Estimates Using Panel Data," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 2(1), pages 1-1.
    35. 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.
    36. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-363, July.
    37. Tommaso Agasisti & Geraint Johnes, 2009. "Beyond frontiers: comparing the efficiency of higher education decision-making units across more than one country," Education Economics, Taylor & Francis Journals, vol. 17(1), pages 59-79.
    38. Avkiran, Necmi K., 2001. "Investigating technical and scale efficiencies of Australian Universities through data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 35(1), pages 57-80, March.
    39. Kristof De Witte & Laura López-Torres, 2017. "Efficiency in education: a review of literature and a way forward," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 339-363, April.
    40. Kuo, Jenn-Shyong & Ho, Yi-Cheng, 2008. "The cost efficiency impact of the university operation fund on public universities in Taiwan," Economics of Education Review, Elsevier, vol. 27(5), pages 603-612, October.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Higher Education Efficiency; Efficiency Frontier Methods; Stochastic Frontier Analysis; Data Envelopment Analysis;

    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cem:doctra:708. 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: (Valeria Dowding). General contact details of provider: http://edirc.repec.org/data/cemaaar.html .

    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.