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Measuring efficiency in education: an analysis of different approaches for incorporating non-discretionary inputs

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  • Jose Manuel Cordero-Ferrera
  • Francisco Pedraja-Chaparro
  • Javier Salinas-Jimenez

Abstract

Measuring efficiency in the education sector is a highly complex task. One of the reasons is that the main resource of schools (the type of students they have) lie outside of their control, which means that it must be treated differently to other factors in analysis. This study examines the different options available in the literature for incorporating non-controllable inputs in a data envelopment analysis in order to determine the most appropriate model for evaluating schools. Our empirical study presents the results obtained using the model proposed by Fried et al. (1999), though we use bootstrap techniques to avoid problems of bias in the estimations.

Suggested Citation

  • Jose Manuel Cordero-Ferrera & Francisco Pedraja-Chaparro & Javier Salinas-Jimenez, 2008. "Measuring efficiency in education: an analysis of different approaches for incorporating non-discretionary inputs," Applied Economics, Taylor & Francis Journals, vol. 40(10), pages 1323-1339.
    • Handle: RePEc:taf:applec:v:40:y:2008:i:10:p:1323-1339
    DOI: 10.1080/00036840600771346
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    References listed on IDEAS

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    1. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 1993. "The Measurement of Productive Efficiency: Techniques and Applications," OUP Catalogue, Oxford University Press, number 9780195072181.
    2. Mei Xue & Patrick T. Harker, 1999. "Overcoming the Inherent Dependency of DEA Efficiency Scores: A Bootstrap Approach," Center for Financial Institutions Working Papers 99-17, Wharton School Center for Financial Institutions, University of Pennsylvania.
    3. Afonso, Antonio & St. Aubyn, Miguel, 2006. "Cross-country efficiency of secondary education provision: A semi-parametric analysis with non-discretionary inputs," Economic Modelling, Elsevier, vol. 23(3), pages 476-491, May.
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