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Why have UK universities become more indebted over time?

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  • Bell, Adrian R.
  • Brooks, Chris
  • Urquhart, Andrew

Abstract

Media reports of a financial apocalypse facing some UK universities were rife around the onset of the covid-19 pandemic, with much of the blame for their apparently perilous monetary situation levelled at excessive borrowing. This study examines the extent to which higher education institutions in the UK have become more indebted over the past decade and determines the factors that explain why some universities have borrowed more than others. We find that universities with vice chancellors who are older, higher paid, and who have been in their roles for a shorter time, on average have greater levels of indebtedness. We do not observe significant relationships with institutional borrowing for the gender of the vice chancellor, or their previous experience as a deputy vice chancellor or having previously held the top role elsewhere. Among university characteristics, only the level of total assets has any explanatory power for indebtedness, and not its overall institutional ratings score, whether it is a member of the Russell Group, or its total number of students.

Suggested Citation

  • Bell, Adrian R. & Brooks, Chris & Urquhart, Andrew, 2022. "Why have UK universities become more indebted over time?," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 771-783.
    • Handle: RePEc:eee:reveco:v:82:y:2022:i:c:p:771-783
    DOI: 10.1016/j.iref.2022.08.008
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    2. Khoo, Shee-Yee & Perotti, Pietro & Verousis, Thanos & Watermeyer, Richard, 2024. "Vice-chancellor narcissism and university performance," Research Policy, Elsevier, vol. 53(1).

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    JEL classification:

    • I22 - Health, Education, and Welfare - - Education - - - Educational Finance; Financial Aid
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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