Three levels of education and the economic growth

ABSTRACT

The aim of this article is to solve the question how the three main stages of education contribute to the labour productivity growth in selected 125 countries in the period 1999–2014. The model is based on the neoclassical production function enhanced with human capital. The authors draw on the Penn World Tables 9.0 and UNESCO databases. The key benefit of this article is that human capital is characterized according to the returns to education from average number of years of formal schooling at the primary, secondary and tertiary level. Based on the panel data analysis, the contributions of capital and of the three levels of education to the growth of labour productivity are estimated. At the same time, the model allows to estimate the contribution of total factor productivity. The results of the analysis show that tertiary education has the strongest impact on labour productivity across the considered economies. At the same time, the breakdown of aggregate human capital by level of education leads to better clarification of the effects of human capital and physical capital on labour productivity. The conclusions also indicate a tendency towards rising returns to scale induced by the secondary and tertiary education.

KEYWORDS:

• Human capital
• physical capital
• economic growth
• education
• total factor productivity

JEL CLASSIFICATION:

• I25
• J24
• O47

Acknowledgements

The article was prepared with an institutional support of the long-term conceptual development of the Faculty of Economics, Technical University of Liberec, in the framework of the project Excellent Research Teams – Regional Development of the Czech Republic in the Context of the Onset of the Fourth Industrial Revolution.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ The school life expectancy measures the number of years of formal education an average child of the school-entering age would receive during the lifetime if the school enrolment rates remained the same as they are today. It calculates the average number of years an eligible person spent at school during the whole life and thus is an appropriate data source for approximation of the human capital stock in population (UNESCO 2016).

² Unfortunately, the large variety of capital assets makes it currently impossible to get internationally comparable data on the flow of capital services in a sufficiently long time-series and for a sufficient number of countries. Thus, also the main data source for this article, the Penn World Tables 9.0, reports capital stock data, rather than flows of capital services.

³ On the contrary, Klenow and Rodriguez-Clare (1997) and Hall and Jones (1999) assume labour augmenting technological progress and express output per worker as a function of the ratio capital/output (K/Y). The substantial difference between the two approaches is the power of A: it is equal to 1 in case of Hicks-neutrality, while it is equal to (1 – α) in case of Harrod-neutrality. As shown by Gundlach, Rudman, and Wößmann (2002), in the decomposition of output, the assumption of Harrod-neutrality gives more weight to technology, fundamentally because of the fact that any increase of technology, which originates also a variation of capital, is attributed to productivity instead of capital (since (K/Y) does not change).

⁴ This slightly changes Equation (2). Since we apply the econometric approach to the TFP, we can still write Equation (3) as it is, only α₀ is now equal to ln(A) – (1 – α_{K –} α_H)ln(L). But we will still estimate the total value of α₀.

⁵ According to the OECD (2015) data, the average tertiary education premium for the OECD countries is about 60% for an average tertiary education duration of 3.93 years, which means an annual revenue of 12.7% (compared to 6.4% according to Psacharopoulos (1994) for a total education duration in excess of 8 years). Other research, carried out by Maršíková and Kocourek (2012), estimates the tertiary education wage premium at about 8.45% in the United Kingdom, Poland and the Czech Republic. However, the analytical work of Psacharopoulos (1994) is the most widely accepted estimate of returns to education, used also by the Penn World Tables 9.0.

Additional information

Funding

This work was supported by the Technická Univerzita v Liberci, Faculty of Economics [Excellent Research Teams – Regional Development].