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Rankings and university performance: a conditional multidimensional approach

Author

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  • Cinzia Daraio

    () (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza")

  • Andrea Bonaccorsi

    () (Department of Electrical Systems and Automation, University of Pisa, Italy)

  • Leopold Simar

    () (Institute of Statistics, Biostatistics et Actuarial Sciences, Universite' Catholique de Louvain, Louvain-la-Neuve, Belgium)

Abstract

University rankings are the subject of a paradox: the more they are criticized by social scientists and experts on methodological grounds, the more they receive attention in policy making and the media. In this paper we attempt to give a contribution to the birth of a new generation of rankings, one that might improve on the current state of the art, by integrating new kind of information and using new ranking techniques. Our approach tries to overcome four main criticisms of university rankings, namely: monodimensionality; statistical robustness; dependence on university size and subject mix; lack of consideration of the input-output structure. We provide an illustration on European universities and conclude by pointing on the importance of investing in data integration and open data at European level both for research and for policy making.

Suggested Citation

  • Cinzia Daraio & Andrea Bonaccorsi & Leopold Simar, 2014. "Rankings and university performance: a conditional multidimensional approach," DIAG Technical Reports 2014-09, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
  • Handle: RePEc:aeg:report:2014-09
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    References listed on IDEAS

    as
    1. Daraio, Cinzia & Simar, Léopold, 2014. "Directional distances and their robust versions: Computational and testing issues," European Journal of Operational Research, Elsevier, vol. 237(1), pages 358-369.
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    Keywords

    Rankings; European universities; DEA; conditional directional distances; robust frontiers; bootstrap;

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