Determinants of Education System in OECD Countries

Author Name(s): Julia A. Varlamova*, Natalyia I. Larionova
Author Email: Julia.Varlamova@kpfu.ru

Abstract

The education system is subjected to the influence of macroeconomic factors and environmental shocks, under the influence of which the effectiveness and the efficiency of the analyzed social subsystem changes. The purpose of the study is to determine the factors that influence the population number with a certain level of education. Financial macroeconomic indicators and labor market indicators are tested among the regressors.

The results of the study based on the development of panel data models for 30 OECD countries during the period of 2000-2016 show that the higher education system is significantly influenced by financial macroeconomic indicators, while the secondary education system is more influenced by labor market indicators. The long-term interest rate was insignificant both for the model built for higher education and for secondary education model, which can be explained by the relatively low level of the indicator in OECD countries.

The model with fixed effects is built for higher education system. This model takes into account the individual effects of OECD countries. The choice is made for upper secondary education, based on statistical tests, in favor of the model with random effects, which indicate a relative unification of this stage of education in OECD countries.

The conclusions of the study are of practical interest for decision-making at the state level.

Introduction

Higher education is a social institution that promotes the development of human capital of a certain quality. The influence of higher education on the country economic development is realized in various aspects. The effects of higher education on the macroeconomic level are manifested in productivity growth, in GDP growth (Blundell 1999, Sianesi and Van Reenen 2003, Bloom et al. 2006), in the distribution of sustainable development values (Cortese 2003, Kolesnikova et al., 2016).

The system of higher education, in its turn, is the part of a more complex system of social life and is subject to the influence of environmental factors. Various indicators are examined as the macroeconomic factors influencing the system of higher education. Dima et al. (2017) identify Gross Domestic Product (GDP), Research and Development (R & D) investment level, government expenditure on education, exports of high-tech, costs of exploiting intellectual property. The authors examine the influence of macroeconomic factors on the convergence of higher education systems in Europe.

Menon et al. (2016) group the factors which influence the demand for private higher education, in the following way: economic, social, institutional and individual ones. According to the results of their research, the place of residence does not influence the aspiration of school leavers to obtain higher education. Besides, the financial crisis has influenced the perception of return rate on higher education by students.

The traditional relationship between the labor market and higher education is indicated in a number of studies where easy access to higher education, on the one hand, leads to a higher productivity of the country economy, but, on the other hand, causes mass unemployment in a number of countries like Europe (Tribe 2003 ), and the East Asian countries (Yang and Chan 2017). Green and Henseke (2016) examining the graduate underemployment in 21 OECD countries concluded that higher education creates disproportions in the labor market, however, it has certain advantages of the social plan.

The impact between such a macroeconomic indicator as the level of savings and the training system can also be analyzed from two sides. A significant number of studies have been devoted to the analysis of training program impact on the individual savings behavior (Solmon 1975, Bernheim et al. 2001, Lusardi 2009). The aspect of targeted saving stimulation aimed at the payment for education and higher education is disclosed in the work by Hossler and Vesper (1993). The authors analyze the factors that affect the savings of parents in order to pay higher education.

Loans can be seen as negative savings. Best and Keppo (2014) conclude that the demand for higher education is influenced by higher education prices, but a high correlation of prices with borrowing leads to the fact that credit restrictions act as a financial barrier to increase the number of higher education students.

Conclusions

The education system is closely related to the economic system of society and is influenced by macroeconomic factors. The review of literature showed that research is aimed mainly at the analysis concerning the impact of the education system on the country economic development and its significant social effects. However, the scientific and practical interest from the point of view of public policy is the identification of the factors that influence the education systems of countries.

The results of a study based on the construction of panel data models for 30 OECD countries during the period 2000-2016 revealed that the higher education system is significantly influenced by financial macroeconomic indicators, while the secondary education system is more influenced by labor market indicators. The long-term interest rate was insignificant both for the model built for higher education and for the model of secondary education, which can be explained by the relatively low level of the indicator in OECD countries.

Summary

The efficiency and effectiveness of the education system is influenced by macroeconomic factors, such as financial indicators that characterize the population income, their stability and the ability of use for other purposes than consumption. The number of people with upper secondary education is influenced by labor market indicators. Thus, when you carry out public policies aimed at higher education system support, the priority should be given to financial support of population, while the upper secondary education system is influenced by labor market indicators.

Acknowledgements

The work is performed according to the Russian Government Program of Competitive Growth of Kazan Federal University.

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