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Some university students are more equal than others: Evidence from England

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  • C F Chen
  • K T Soo

Abstract

This paper estimates the efficiency of students in English universities using Data Envelopment Analysis (DEA) and a new dataset which is able to capture the behaviour of university students. Taking as the output the classification of a university degree, we use as inputs teaching hours and quality, entry qualifications, and the effort level. We find that university students differ in terms of the efficiency with which they use inputs in producing good degrees. In a second stage, we explore the determinants of the efficiency of university students using a truncated regression model. Higher student efficiency is found to be positively and significantly related to university size, and negatively and significantly related to the proportion of part-time students and the number of academic staff. The quality of a university has no significant impact on the efficiency of its students once endogeneity of university quality is controlled for.

Suggested Citation

  • 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.
  • Handle: RePEc:lan:wpaper:600480
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    File URL: http://www.lancaster.ac.uk/media/lancaster-university/content-assets/documents/lums/economics/working-papers/UniversityStudents.pdf
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    References listed on IDEAS

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    1. Luca Stanca, 2006. "The Effects of Attendance on Academic Performance: Panel Data Evidence for Introductory Microeconomics," The Journal of Economic Education, Taylor & Francis Journals, vol. 37(3), pages 251-266, July.
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    3. Jill Johnes, 2006. "Measuring Efficiency: A Comparison of Multilevel Modelling and Data Envelopment Analysis in the Context of Higher Education," Bulletin of Economic Research, Wiley Blackwell, vol. 58(2), pages 75-104, April.
    4. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    5. J Johnes, 2006. "Efficiency and productivity change in the English higher education sector from 1996/97 to 2002/03," Working Papers 575369, Lancaster University Management School, Economics Department.
    6. Johnes, Jill, 2006. "Data envelopment analysis and its application to the measurement of efficiency in higher education," Economics of Education Review, Elsevier, vol. 25(3), pages 273-288, June.
    7. Edward P. Lazear, 2001. "Educational Production," The Quarterly Journal of Economics, Oxford University Press, vol. 116(3), pages 777-803.
    8. Johnes, Jill, 2006. "Measuring teaching efficiency in higher education: An application of data envelopment analysis to economics graduates from UK Universities 1993," European Journal of Operational Research, Elsevier, vol. 174(1), pages 443-456, October.
    9. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    10. Fare, Rolf & Grosskopf, Shawna & Norris, Mary, 1997. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries: Reply," American Economic Review, American Economic Association, vol. 87(5), pages 1040-1043, December.
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