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Does it matter How We Measure Congestion?

Author

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  • Tony Flegg

    () (School of Economics, University of the West of England)

  • David O. Allen

    (School of Economics, University of the West of England)

Abstract

This paper examines three alternative methods of measuring congestion, from both theoretical and empirical perspectives. These methods are the conventional approach of Färe and Grosskopf, the alternative proposed by Cooper et al., and a new method developed by Tone and Sahoo. Each method is found to have merits and demerits. The properties of the different methods are examined using data for 41 ‘new’ British universities in the period 1995/6 to 2003/4. Contrary to expectations, Färe and Grosskopf’s approach generally indicates substantially more congestion than do the other procedures. The main reason for this is identified as being its use of CRS rather than VRS as the assumed technology. While the alternative measures of congestion are found to be positively correlated, the correlations are not strong enough for them to be regarded as substitutes. All methods suggest the existence of a widespread problem of congestion in the new universities, although they differ noticeably as regards its severity.Length: 37 pages

Suggested Citation

  • Tony Flegg & David O. Allen, 2006. "Does it matter How We Measure Congestion?," Working Papers 0614, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
  • Handle: RePEc:uwe:wpaper:0614
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    File URL: http://carecon.org.uk/DPs/0614.pdf
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    References listed on IDEAS

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    1. Cooper, William W. & Seiford, Lawrence M. & Zhu, Joe, 2000. "A unified additive model approach for evaluating inefficiency and congestion with associated measures in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 34(1), pages 1-25, March.
    2. Cherchye, Laurens & Kuosmanen, Timo & Post, Thierry, 2001. "Alternative treatments of congestion in DEA: A rejoinder to Cooper, Gu, and Li," European Journal of Operational Research, Elsevier, vol. 132(1), pages 75-80, July.
    3. Rolf Färe & Shawna Grosskopf, 2000. "Research Note. Decomposing Technical Efficiency with Care," Management Science, INFORMS, vol. 46(1), pages 167-168, January.
    4. Tone, Kaoru & Sahoo, Biresh K., 2004. "Degree of scale economies and congestion: A unified DEA approach," European Journal of Operational Research, Elsevier, vol. 158(3), pages 755-772, November.
    5. Cooper, W. W. & Gu, Bisheng & Li, Shanling, 2001. "Comparisons and evaluations of alternative approaches to the treatment of congestion in DEA," European Journal of Operational Research, Elsevier, vol. 132(1), pages 62-74, July.
    6. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    7. Cooper, W. W. & Deng, Honghui & Huang, Zhimin M. & Li, Susan X., 2002. "A one-model approach to congestion in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 36(4), pages 231-238, December.
    8. Fare, R. & Grosskopf, S. & Logan, J., 1985. "The relative performance of publicly-owned and privately-owned electric utilities," Journal of Public Economics, Elsevier, vol. 26(1), pages 89-106, February.
    9. Oulton,Nicholas & O'Mahony,Mary, 1994. "Productivity and Growth," Cambridge Books, Cambridge University Press, number 9780521453455, May.
    10. 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.
    11. Tony Flegg & David O. Allen, 2006. "Are the New British Universities Congested?," Working Papers 0610, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    12. Fare, Rolf & Grosskopf, Shawna, 2000. "Slacks and congestion: a comment," Socio-Economic Planning Sciences, Elsevier, vol. 34(1), pages 27-33, March.
    13. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    14. A. T. Flegg & D. O. Allen & K. Field & T. W. Thurlow, 2004. "Measuring the efficiency of British universities: a multi-period data envelopment analysis," Education Economics, Taylor & Francis Journals, vol. 12(3), pages 231-249.
    15. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    16. P. Byrnes & R. Färe & S. Grosskopf, 1984. "Measuring Productive Efficiency: An Application to Illinois Strip Mines," Management Science, INFORMS, vol. 30(6), pages 671-681, June.
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    Keywords

    Data envelopment analysis; Education; Congestion;

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