Investments in Higher Education and the Economic Performance of OECD Member Countries

1. Investments in Higher Education and the Economic Performance of OECD Member Countries 5th Bi-National Regional Science Workshop Tel Aviv, 29-30/4/2007 Amnon Frenkel Eran Leck Faculty of Architecture & Town Planning Technion – Israel Institute of Technology

2. Direct Benefits: • Enhancement of GDP, employment, and labor productivity • Enlargement of the pool of skilled scientists and engineers • Indirect Benefits: • Capital investments • Creation and adoption of technological innovations The contribution of Universities and Academic Research to the Economy Nelson, 1986; Jaffe, 1989; Adams, 1993; Fischer and Varga, 2003. • Types of contributions of higher education to economic growth(Martin et al., 1996): • Increasing the stock of useful knowledge • Promoting knowledge spillovers • Training highly skilled graduates • Creating methodologies and new scientific tools • Increasing the capability for scientific and technological problem-solving.

3. Criticism: • Difficulties in finding reliable indicators of technological change • Econometric difficulty in drawing conclusions from non-experimental data • The models do not explain the association between higher education (or basic research) and economic performance in a direct way Econometric Growth Regression Studies Chatterji (1988); Adams (1990, 1993); McMahon (1993); Guellec and van Pottelsberge de la Potterieu (2001); Sianesi and Reenen (2003).

4. To investigate the association between higher education investments and economic growth in OECD countries. Hypothesis – a positive and significant relationship exists between higher education investments and the economic performance of developed countries Research Objective Models Indirect model - Two-stage, least-squares regression model Direct model -Multivariate regression models.

5. The 30 OECD countries + Israel. Investigation Unit Data Bases • Electronic database of the World Bank (WDI) • Science and Technology Indicators of the OECD • Electronic databases of UNESCO and the OECD • LABORSTA (International Labor Organization Bureau of Statistics)

6. Stage 1 - higher education investments in technological and scientific research – X (input) contribute to the training of a skilled, technological labor force – Y (output). [1] Y= f(X) Stage 2 - Skilled labor force - Y (input) is translated into higher productivity and growth rates - Z (output) [2] Z= f(Y) Two-stage - least-squares regression model

7. Stage 1Human Capital Quality as a Function of higher education investments

8. Regression Results – Stage 1 ** Significant at the 1% level * Significant at the 5% level

9. Percentage of employees in the computer field as a function of total expenditure per student in research universities Strong and statistically significant relationship exists between the per student expenditurein research universities, and the percentage of employees in the computer field in the country

10. Percentage of employees in scientific and technological fields as a function of the expenditure per student on R&D The more the country invests in universities’ R&D, the greater will be the percentage of employees in the computer, scientific, and technological fields

11. Stage 2Economic Performance as a Function of Human Capital Quality

12. Regression Results – Stage 2 ** Significant at the 1% level * Significant at the 5% level

13. GDP per capita as a function of the percentage of employees in scientific and technological fields A positive and significant link exists between the percentage of employees in scientific and technological fields and the GDP per capita

14. The linkage between the two stages Does a significant and positive association also exist between higher education and economic performance? A simultaneous equation model is formulated, using the seemingly unrelated regression (SUR) method.

15. The SUR Model: (1) (2) the second index in each parameter represents the equation number OLS and SUR Results for Model B Figures in parentheses are the standard error ** Significant at the 1% level * Significant at the 5% level

16. Multivariate Model

17. Multivariate models describing the association betweenhigher education variables and per-capita GDP (PPP) ** Significant at the 1% level. * Significant at the 5% level.

18. GDP per capita PPP as a function of the expenditures on R&D and instruction in research universities (log-linear model) ** Significant at the 1% level. * Significant at the 5% level. A one percent increase in expenditure on R&D (per student) in research universities and a one percent increase in expenditure on instruction in higher education institutions (measured as a percentage of GDP) may contribute to a rise of 0.78% in the GDP.

19. Point Elasticities - per-capita GDP in relation to the expenditure on R&D in research universities • A clear spatial dimension, with Western European countries (e.g., Sweden, Germany, the Netherlands, UK, Austria, Finland) presenting much higher point elasticities than Eastern European countries (Hungary, Poland, Slovakia and Turkey). • Smaller countries (Sweden, Israel, the Netherlands, Austria, and Finland) have higher point elasticities than do big countries (Unites States, France).

20. 1) 2) 3) 4) Schematic Description of the model R&D Expenditure Simultaneous Model Percentage of Employees in the computer field GDP Per Capita Instruction Expenditure

21. OLS and SUR Results

22. Conclusions • The findings of the simultaneousmodel support our hypothesis regarding a two-stage process between higher education investments and economic growth. • Higher education investments and scientific and technological research make a significant contribution to the economic performance of OECD countries • The two main activities of universities – teaching and research--were found to be connected to the ability of OECD countries to enhance their per-capita GDP • Small countries see a vital need to constantly reassess the degree of innovation of their economies in order to sustain economic competitiveness. • Small countries must think imaginatively in order to overcome their own limitations, whether in size or resource. • Investments in a technologically skilled labor force become a feature of paramount importance in national and strategic economic planning.