Higher education and growth


Higher education has been a key issue in recent public debates in France.

ByPhilippe d'Arvisenet

Topics have ranged from the mediocre results of research to the excessive development of branches with few hiring opportunities, a “selection by failure” system rather than one based on better career counselling, and the problems of governance. Another hot topic is the low level of resources for higher education (spending per student) compared to other OECD countries and – another French exception – even when compared to investment in secondary education![1]We focus on higher education’s role in fostering productivity gains and boosting growth potential. The level of education of the working-age population plays a crucial role in determining growth rates and productivity gains. The skills of the population shape the country’s ability to innovate and to tap technological innovation. Based on observations in 60 countries over the past four decades, Hanushek and Woessmann (2007) demonstrate a robust relationship between GDP growth per capita and the average number of years in education of the working-age population (15-64 age group). Yet, the quality of education, as measured by the results of standardised scholastic tests, seems to have a much more significant impact than the average duration of education. After taking into account an education quality indicator, the correlation coefficient rose to 0.73 from 0.33! The authors also show that the impact of this education quality factor is stronger in countries that are very open (see appendix 1). Krueger and Lindahl (2001) obtained similar results based on a panel of 110 countries. They show that the impact of increasing the level of education is hardly visible in the short term (5 years), but becomes very significant from a 10 to 20-year horizon (see appendix 2). Research conducted by endogenous growth theorists in recent years show that school systems and education policies that were appropriate during catch-up phases (such as the period 1946-1975 in France) cease to be so as the country approaches the technology frontier[2]. During catch-up phases, it is important to have a workforce that is sufficiently educated at the primary and secondary levels to use existing technologies (imitation policies). Yet once a country begins to approach the technology frontier, the capacity to innovate becomes crucial, which means giving priority to higher education. This has become even more important with the emergence of a series of general-purpose technologies, which required further innovation to apply these new technologies to specific sectors. Using a panel of OECD countries, G. Cette (2007) shows that there is a significant positive correlation between the share of university graduates in the working-age population and the investment rate in new information and communications technologies (ICT). For example, in countries like the United States, Sweden, Finland and Denmark, where over 30% of the working-age population has a degree in higher education, the ICT investment rate exceeds 3.5%. At the other extreme, in Italy and Portugal, where less than 15% of the working-age population have university degrees, the ICT investment rate is less than 2.5%. A similar correlation exists with the proportion of households with internet connections: 55% in the United States, 70% in Denmark and at the other extreme, only 35% in Italy and 25% in Portugal (using 2004 data).[3] Productivity and education: a few results Total factor productivity of capital and labour (denoted A) reflects the efficiency of the use of the production factors. It can increase through the imitation of existing technologies or through innovation. If A* is productivity at the technology frontier, then:  

The first component on the right hand side of the equation corresponds to the imitation effect, the second to innovation between periods t-1 and t. The distance from the technology frontier can be measured by dt

Using g as the growth rate of productivity at the technology frontier, we can divide the terms of the equation by A* to obtain:

d moves from 0 to 1 as the country approaches the technology frontier. When d is close to zero, imitation is the main source of productivity gains, but as d moves towards 1, innovation plays an increasingly important role. This illustrates the importance of setting up education and research structures that foster innovation (Acemoglu, 2002). Using empirical data from 80 countries between 1960 and 2000, Aghion et al. (2003) studied the impact of education on productivity by distinguishing between primary and secondary education on the one hand and higher education on the other. They show that there is a differentiated effect for each level of education, depending on the country’s distance from the technology frontier. Their results are summarised in the table 1.

An additional year of higher education increases the growth of total factor productivity by 8%. The variable st * dtf t-1 has a significant positive impact, which demonstrates the increasing importance of higher education for growth as the country approaches the technology frontier. Using a selection of OECD countries, Aghion et al (2004) distinguishes between the impact of higher education (undifferentiated) and that of at least 2 years of higher education (the share of the working-age population with a short undergraduate education is added to the general population with no higher education). They conclude that a long period of higher education (over 2 years) has a much more significant impact on productivity (see table 2). They stress that toward the end of the 1970s, France crossed the point where it “became more effective to invest in higher education than to invest in secondary education.” Using a panel of 21 OECD countries, l’Angevin et al. (2005) reach the same conclusions as Aghion et al. The authors estimate the elasticity of productivity to human capital at 0.11 in France vs an OECD average of 0.07. Furthermore, by distinguishing between several levels of education (through middle school, short technical degree, short higher education and long higher education) they show that only a short technical degree and long higher education had a positive impact on productivity gains. Moreover, this effect does not last long for short technical degrees, but persists over the long term for longer periods of higher education. All in all, policies that develop long higher education (which generally coincide with policies in favour of innovation) have a bigger impact on long-term productivity than those that encourage short technical training. We can thus see why it is important to make the university system more attractive for many good high-school graduates, who, under the current situation, are being steered towards short, selective technical sectors. To use Mr. Aghion’s terminology, these technical programmes encourage imitation policies, whereas what countries close to the technology frontier, such as France, need are innovation policies. Does increasing the pool of skilled labour with university degrees put downward pressure on relative wages for skilled jobs? In other words, does it reduce the advantages of a higher education in terms of relative wages for skilled workers (ratio of skilled wages/average wages)? Looking at the US experience from the 1960s to the present, according to several studies the answer is no. Although the increase in the skilled labour pool at the end of the 1960s and in the 1970s did squeeze the relative pay of graduates, the same does not apply since the 1980s. Acemoglu (1998, 2002) charts this phenomenon, which we have outlined below (see chart below). In the short term, for a given technology, an extra supply of qualified labour (DS) lowers the relative wage from W0 to W1 (shift along the curve of short-term demand DS1). During a later period, the abundance of skilled labour encourages companies to adopt more advanced technologies among those available (DS1 shifts to the right to DS2), a trend that limits the moderation of relative wages for skilled labour.[4] In the longer term, the abundance of skilled labour stimulates technical progress, resulting in a positive slope for the curve of long-term demand for skilled labour (DL2), since this stimulates demand for this type of labour and pushes up relative wages (W2). (See Schema)

Philippe d’Arvisenet


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