The effects of Bologna Process on expenditure in HE systems of EU-15 countries

1. The effects of Bologna Process on expenditure in HE systemsof EU-15 countries 30 th Annual EAIR Forum (Copenhagen 2008) Tommaso Agasisti (Politecnico di Milano, Italy) Carmen Pérez Esparrells (UAM, Spain) Giusepe Catalano (Politecnico di Milano, Italy) Susana Morales Sequera (UAM, Spain)

2. Agenda • Motivation • Objectives • Methodology and data • Results • Conclusions

3. The motivation • Education => economic growth • Patterns of HE expenditure • Bologna process => process of convergence of educational policy (the objective: implementation of EHEA with common characteristics by the end of 2010)

4. The context • Bologna Process: some characteristics • The idea has fully overcome the first expectations. Why? • Educational dimension => we are in the line of convergence • Economic dimension => convergence? (our research question) • Social dimension => the new challenge

5. Objectives • Analysis of indicators of financial resources invested in HE (1998-2004) and verifying if is there a process of convergence in expenditure per student in HEIs. • Estimating if the wealth of countries (measured by GDP per capita) has influenced the process of convergence.

6. Data • Dependent variable: Expenditure per student • Determinants: • GDP per capita; • % population who attained tertiary education; • expenditure for HE as %GDP • public funds to HE as a % of total HE expenditure • “Bologna effect” (dummy) SOURCE: OECD data (Education at a Glance from 2002 to 2007)

7. Methodology Two approaches: • Regression analysis: fixed-effects and random-effects to detect a “Bologna effect” • Convergence analysis: • Absolute convergence (β-convergence) • Conditional β-convergence • σ-convergence

8. σ-convergence • The most important measure of cross-section analysis of dispersion that has been used: coefficient of variation (Barro & Salas-i-Martin). • σ-convergence occurs if dispersion among countries falls in time.

9. β-convergence • A process of absolute convergence (β-convergence) exists if countries with lower expenditure per student in HEIs levels have grown to higher rates than countries with better levels. • β-convergence is calculated with the estimation of β in the following regression: • β-convergence will exist if parameter β is positive and statistically significant

10. Conditional β-convergence • In many situation an absolute convergence (β-convergence) cannot take place since there are different structural conditions between the different countries, so that they do not converge at a unique equilibrium point. There is absolute convergence if regions have the same starting level. • In these cases, we use what Sala-i-Martin (1996), Barro and Sala-i-Marti (1992) and Mankiw, romer and Weil (1992) denominated conditional convergence (including an other explanatory variable).

11. Results of regression analysis

12. Results of σ-convergence Source: authors’ elaboration

13. Results of β-convergence Notes: t-Statistic in parenthesis. The coefficients are statistically significant with a confidence of 90%(*) or 95%(**).

14. Results of β-convergence in the entire period • All the estimated parameters are statistically significant . • β positive informs about absolute convergence. • The goodness of fit is only 21.35%, which indicate scarce relation between both variables. However, in the period 2001-2004 is 34%.

15. Results of conditional β-convergence • We also investigated whether convergence in the period 1998-2004 has been affected by national wealth, in this case, GDP per capita. • In consequence, we ran a new estimation of the model including GDP per capita. • The inclusion of GDPpc is only significant in the period 1998-2001 (after that period, the convergence is due to Bologna Process?)

16. Results of conditional β-convergence Notes: t-Statistic in parenthesis. The coefficients are statistically significant with a confidence of 90%(*), 95%(**) or 99%.

17. Results of conditional β-convergence • The introduction of GDPpc in the period 1998-2001 increases significantly the estimated parameters and increases the goodness of fit until 43.75%. • In this period the growth rate of expenditure per student had been influenced by the level of GDPpc • Countries have converged to different stationary states; that is, GDPpc variable explains cross-country patterns of growth in expenditure per capita in this period, before Bologna Process.

18. Conclusions The results of “financial” convergence for all the period (1998-2004) are clear and they are going in the “right” direction. We show evidence of an approaching process in the composition of HEIs expenditure per student in EU-15 countries. We have also identified that this convergence was more marked in the second part of the observation period, after Bologna process. New research: with data until 2010 what’s happen in the long term? Maybe, these difference in terms of expenditure per student will be less for a “natural” process

19. Conclusions The role of private sector in explaining the convergence in expenditure per student