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Measuring Efficiency: A Comparison of Multilevel Modelling and Data Envelopment Analysis in the Context of Higher Education

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  • Jill Johnes

Abstract

Data envelopment analysis (DEA) and multilevel modelling (MLM) are applied to a data set of 54,564 graduates from UK universities in 1993 to assess whether the choice of technique affects the measurement of universities' performance. A methodology developed by Thanassoulis and Portela (2002; Education Economics, 10(2), pp. 183-207) allows each individual's DEA efficiency score to be decomposed into two components: one attributable to the university at which the student studied and the other attributable to the individual student. From the former component, a measure of each institution's teaching efficiency is derived and compared to the university effects from various multilevel models. The comparisons are made within four broad subjects: pure science, applied science, social science and arts. The results show that the rankings of universities derived from the DEA efficiencies which measure the universities' own performance (i.e., having excluded the efforts of the individuals) are not strongly correlated with the university rankings derived from the university effects of the multilevel models. The data were also used to perform a university-level DEA. The university efficiency scores derived from these DEAs are largely unrelated to the scores from the individual-level DEAs, confirming a result from a smaller data set (Johnes, 2006a; European Journal of Operational Research, forthcoming). However, the university-level DEAs provide efficiency scores which are generally strongly related to the university effects of the multilevel models. Copyright Blackwell Publishers Ltd and the Board of Trustees of the Bulletin of Economic Research, 2006.

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Bibliographic Info

Article provided by Wiley Blackwell in its journal Bulletin of Economic Research.

Volume (Year): 58 (2006)
Issue (Month): 2 (04)
Pages: 75-104

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Handle: RePEc:bla:buecrs:v:58:y:2006:i:2:p:75-104

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Cited by:
  1. Angel García Correas & Manuel Larran Jorge, 2010. "Análisis de diferentes medidas de la eficiencia investigadora y factores explicativos en las universidades públicas españolas," Investigaciones de Economía de la Educación volume 5, in: María Jesús Mancebón-Torrubia & Domingo P. Ximénez-de-Embún & José María Gómez-Sancho & Greg (ed.), Investigaciones de Economía de la Educación 5, edition 1, volume 5, chapter 36, pages 703-732 Asociación de Economía de la Educación.
  2. Deutsch, Joseph & Dumas, Audrey & Silber, Jacques, 2013. "Estimating an educational production function for five countries of Latin America on the basis of the PISA data," Economics of Education Review, Elsevier, vol. 36(C), pages 245-262.
  3. Jean-Charles Billaut & Denis Bouyssou & Philippe Vincke, 2010. "Should you believe in the Shanghai ranking?," Post-Print hal-00388319, HAL.
  4. C F Chen & K T Soo, 2009. "Some university students are more equal than others: Evidence from England," Working Papers 600480, Lancaster University Management School, Economics Department.
  5. Tzeremes, Nickolaos & Halkos, George, 2010. "A DEA approach for measuring university departments’ efficiency," MPRA Paper 24029, University Library of Munich, Germany.
  6. Billaut, Jean-Charles & Bouyssou, Denis & Vincke, Philippe, 2010. "Should you believe in the Shanghai ranking? An NCDM view," Economics Papers from University Paris Dauphine 123456789/2947, Paris Dauphine University.
  7. Halkos, George & Tzeremes, Nickolaos, 2011. "Adjusting for cultural effects on countries’ education policy efficiency:an application of conditional full frontiers measures," MPRA Paper 30098, University Library of Munich, Germany.

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