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Outline of the Talk

Higher Education Some International comparisons Domingo Docampo Universidade de Vigo (Spain) On sabbatical at ECE-UNM. Outline of the Talk. World Demand of Higher Education The case of Australia Two models of Higher Education Funding OECD Indicators for the two models

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Outline of the Talk

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  1. Higher EducationSome International comparisonsDomingo DocampoUniversidade de Vigo (Spain)On sabbatical at ECE-UNM

  2. Outline of the Talk • World Demand of Higher Education • The case of Australia • Two models of Higher Education Funding • OECD Indicators for the two models • How to tell the models apart? • ARWU data on research • Comparative performance of countries and US regions • Two conclusions

  3. World’s demand of HE • Enrolment in Higher Education • 97M students in 2000 • 263M in 2025 (predicted) • Mobility in Higher Education • 1.9M foreign in 2000 (2%) • 7.2M in 2025 (3%)

  4. World’s share of international students (2000-05)

  5. Mobility from Asia (1 million)

  6. Asian mobility relative to GDP

  7. Mobility to Australia

  8. What happened in Australia? • Policy Reforms in 1987 • Income-contingent loans • Government change in 1996 • New Higher Education Act 2003 • Changes in Tuition • Internationalization of HE

  9. On Tuition • If tuition was the answer, then what was the question? • Governments felt financially pressured, began to question whether higher education is a public good? • Private benefits do accrue to graduates. • Positive externalities: Good citizens, Good taxpayers. • Debate in Australia 1986 • New Zealand followed suit • UK in 2003 • Taboo in Continental Europe

  10. The case for and against Higher Education as a public good • Education is a basic right • Graduates will return the benefits by paying more taxes (around US$ 200,000 during a lifetime) • Income tax is paid by many more non-graduates than graduates: free higher education is horizontally inequitably • The taxpayer gets a good deal is a dangerous argument (R&D expenses)

  11. Two models • Anglo-American model • Encourages Diversity • Heterogeneous Institutions • Quality comparisons • Scandinavian model • All programs ‘are’ equal • Homogeneous Institutions • Quality of a Public Service

  12. Two approaches to HE Funding • Utopian • Very high taxes • R&D commitment • High Public Spending • High Enrolment • Practical • Much lower taxes • R&D commitment • High Private Spending • High Enrolment

  13. Are there utopian countries? • Is there a way to tell a country apart? • Shouldn’t it be obvious? • Rationalize the obvious using • OECD data • OECD indicators • The Economist and World Bank Indicators

  14. Set of Indicators • Taxes on Average worker (I5) • Enrolment (I6) • Percentage of GDP of: • Public expenditure on Education (I1) • Public expenditure on HE (I2) • Private expenditure on HE (I3) • Total spending on HE (I4) • Gross domestic expenditure on R&D (I7)

  15. Main data Table

  16. Correlation Matrix

  17. Total vs. Public Expenditures

  18. TAXES vs PRIVATE EXPENDITURES

  19. Total Expenditures in HEvs. Enrolment

  20. PRINCIPAL COMPONENTS

  21. PRINCIPAL COMPONENT 1

  22. PRINCIPAL COMPONENT 2

  23. Understanding the data • Normalize indicators: best gets 100 points • Rearrange proportionally • Subtract OECD average • Look at the sign of the correlation • I1, I2 and I5 correlate positively. • I3 correlates negatively with them all. • I4 and I6 correlate positively

  24. A measure for Utopia • M1 first principal component using only I1, I2, I3 and I5 • M2 first principal component using only I4, I6 and I7

  25. The new clustering

  26. LANDING FROM UTOPIA

  27. LANDING FROM THE FUTURE

  28. Quality Assessment • Shanghai Jiao Tong University’s Academic Ranking of World Universities • Based on Scientific Production • Sound Indicators • Reliable Data • Data can be aggregated for countries • Allows international comparisons • It is not the whole story but…

  29. ARWU

  30. CORRELATION MATRIX

  31. HOW GOOD ARE THE BETTER

  32. Cutting the US in European like slices

  33. How good are the better now

  34. Compare only the best university • Given a REGION X, let N(X) be equal to GDP(US)/GDP(X) • Let USX be the median of the first N(X) US universities’ rank. • Let Lag(X) be the difference between the rank of the best university from region X and USX. • Normalize the result lag(X)/USX

  35. Prima Donna (1)

  36. Prima Donna (2)

  37. Prima Donna (3)

  38. Universities in ARWU

  39. HOW GOOD ARE THE BETTER?

  40. CLUSTERING (25-500)

  41. RANKING ACROSS ARWU

  42. From 50 to 500

  43. From 100 to 500

  44. Over-share of GDP (500)

  45. BEST 500 (GDP SHARE)

  46. CORRELATION MATRIX

  47. Sci (500)

  48. Quality vs Quantity (500)

  49. Quality Indicators

  50. Conclusions (1) • There are indeed two models to properly fund Higher Education • Choose one, but please, to the fullest.

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