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An analysis of costs in institutions of higher education in England

  • E Thanassoulis
  • G Johnes
  • J Johnes

Cost functions are estimated, using both random effects and stochastic frontier methods, for institutions of higher education in England. The paper advances on the existing literature by employing finer disaggregation by subject, institution type, and location, and by introducing consideration of quality effects. The findings are that, amongst undergraduates, medical students are the most costly, and non-science students the least; amongst postgraduates, those on taught courses are costly, while research students are relatively inexpensive. Provision in London is found to be more costly than that elsewhere. Estimates of economies of scale and economies of scope vary according to the choice of estimating technique. The random effects model suggests that ray economies of scale and economies of scope are ubiquitous. The stochastic frontier model suggests some product-specific economies of scale in research, but diseconomies elsewhere, and product specific economies of scope in undergraduate science, but diseconomies elsewhere. This has implications for achieving any expansion in higher education.

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File URL: http://www.lancaster.ac.uk/media/lancaster-university/content-assets/documents/lums/economics/working-papers/AnalysisCosts.pdf
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Paper provided by Lancaster University Management School, Economics Department in its series Working Papers with number 566942.

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Date of creation: 2005
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Handle: RePEc:lan:wpaper:566942
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  1. Verry, D W & Layard, P R G, 1975. "Cost Functions for University Teaching and Research," Economic Journal, Royal Economic Society, vol. 85(337), pages 55-74, March.
  2. Geraint Johnes, 1996. "Multi-product cost functions and the funding of tuition in UK universities," Applied Economics Letters, Taylor & Francis Journals, vol. 3(9), pages 557-561.
  3. Philip Andrew Stevens, 2005. "A Stochastic Frontier Analysis of English and Welsh Universities," Education Economics, Taylor & Francis Journals, vol. 13(4), pages 355-374.
  4. Wallace, T D & Hussain, Ashiq, 1969. "The Use of Error Components Models in Combining Cross Section with Time Series Data," Econometrica, Econometric Society, vol. 37(1), pages 55-72, January.
  5. Geraint Johnes, 2004. "A Fourth Desideratum: The CES Cost Function and the Sustainable Configuration of Multiproduct Firms," Bulletin of Economic Research, Wiley Blackwell, vol. 56(4), pages 329-332, October.
  6. Glass, J C & McKillop, Donal G & Hyndman, N, 1995. "Efficiency in the Provision of University Teaching and Research: An Empirical Analysis of UK Universities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(1), pages 61-72, Jan.-Marc.
  7. Izadi, Hooshang & Johnes, Geraint & Oskrochi, Reza & Crouchley, Robert, 2002. "Stochastic frontier estimation of a CES cost function: the case of higher education in Britain," Economics of Education Review, Elsevier, vol. 21(1), pages 63-71, February.
  8. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-32.
  9. Nerlove, Marc, 1971. "A Note on Error Components Models," Econometrica, Econometric Society, vol. 39(2), pages 383-96, March.
  10. Johnes, Geraint, 1997. "Costs and Industrial Structure in Contemporary British Higher Education," Economic Journal, Royal Economic Society, vol. 107(442), pages 727-37, May.
  11. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
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