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Comparing the Efficiency of Italian Public and Private Universities (2007–2011): An Empirical Analysis

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  • Tommaso Agasisti

    () (Politecnico di Milano School of Management)

  • Luisa Ricca

    (IULM University)

Abstract

Abstract The aim of this study is to analyse the technical efficiency of Italian public and private universities. We therefore conduct a Data Envelopment Analysis on Italian universities in the years 2007–2011, using a novel integrated dataset from the Statistical Office of the Ministry of Education and from the National Agency for Evaluation. The inputs of the model are the total number of students and faculty staff, while the outputs are the total number of graduates and the revenues from scientific research. The results show differences related to the type of universities (private universities are relatively more efficient than public ones) and geographical area (Northern universities are relatively more efficient than those of the Centre and South). The Malmquist index, used for a comparison of different years, shows that the overall efficiency of Italian universities has increased in the period examined, particularly thanks to pure efficiency.

Suggested Citation

  • Tommaso Agasisti & Luisa Ricca, 2016. "Comparing the Efficiency of Italian Public and Private Universities (2007–2011): An Empirical Analysis," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 2(1), pages 57-89, March.
  • Handle: RePEc:spr:italej:v:2:y:2016:i:1:d:10.1007_s40797-015-0022-7
    DOI: 10.1007/s40797-015-0022-7
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    References listed on IDEAS

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    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. Tommaso Agasisti & Carsten Pohl, 2012. "Comparing German and Italian Public Universities: Convergence or Divergence in the Higher Education Landscape?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 33, pages 71-85, March.
    3. 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.
    4. Simar, Leopold & Wilson, Paul W., 1999. "Estimating and bootstrapping Malmquist indices," European Journal of Operational Research, Elsevier, vol. 115(3), pages 459-471, June.
    5. 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.
    6. Andrew Worthington, 2001. "An Empirical Survey of Frontier Efficiency Measurement Techniques in Education," Education Economics, Taylor & Francis Journals, vol. 9(3), pages 245-268.
    7. Monaco, Luisa, 2011. "Measuring Italian university efficiency: a non-parametric approach," MPRA Paper 37949, University Library of Munich, Germany, revised 29 Feb 2012.
    8. Aleksandra Parteka & Joanna Wolszczak-Derlacz, 2013. "Dynamics of productivity in higher education: cross-european evidence based on bootstrapped Malmquist indices," Journal of Productivity Analysis, Springer, vol. 40(1), pages 67-82, August.
    9. Dino Rizzi, 2001. "L'efficienza dei dipartimenti dell'Università Ca' Foscari di Venezia via DEA e DFA," ECONOMIA PUBBLICA, FrancoAngeli Editore, vol. 2001(3).
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    1. repec:spr:italej:v:3:y:2017:i:1:d:10.1007_s40797-016-0042-y is not listed on IDEAS

    More about this item

    Keywords

    Efficiency; Higher education; Private universities; Malmquist index;

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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