Dinara Mukhiyayeva

Type of the article: Research Article

Support for the education system is a strategic measure that ensures the long-term development and growth of a country’s economy. Increased funding in this area enables the training of qualified specialists who can adapt to the challenges of the modern economy. In this regard, the purpose of this study is to assess the impact of government spending on education to generate highly intelligent human capital on economic growth in Kazakhstan from 2009 to 2023 using the least squares method, which includes components of government spending on education, as well as the GLS random effects model, which is used to determine the reliability of results. The results show a strong relationship between economic growth and government spending on secondary technical education (0.2393), a moderate relationship between higher education spending (0.0423) and economic development, and a weak relationship between primary education (–0.0050) and economic growth. Thus, a 1-point increase in expenditures for secondary technical education may lead to a 0.2393% increase in GRP, and a 1-point increase in government spending on higher education will lead to a 0.0423% increase in GRP. However, a significant share of government spending is on basic primary education (58%). Based on this, the financing of the education system requires a shift in the financing vector, with a greater focus on higher and secondary technical education, to achieve a more significant impact on economic development.

Acknowledgments
This research is supported by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (AP19680246 “Building up highly intelligent human resources in the conditions of digitalization of the economy of Kazakhstan: problems and prospects”, 2023–2025).

Type of the article: Research Article

Abstract
Innovative and effective territorial development drives the country’s economic growth and its ability to compete on the world stage. The purpose of this paper is to quantify the effectiveness of regional innovative development and to use cluster analysis to identify typological groups of regions and pinpoint priority points of innovative growth. The study’s statistical database consists of official data from the Bureau of Statistics of Kazakhstan for the period 2003–2024. The study used econometric methods such as panel regression, stochastic, and cluster analysis. The results demonstrate that the innovative development of the regions of Kazakhstan is positively influenced by the human resource factor (β = 1.131, p < 0.001) and socio-economic development (β = 1.894, p < 0.001), and negatively influenced by the level of R&D costs (β = –0.473, p = 0.016). The results of the SFA analysis showed that regions with industrial specialization have the most effective innovative development (Pavlodar TE = 0.764, Kostanay TE = 0.751) in the production of innovative products, and that growth may be driven by investments in fixed assets (SFA (β =1.565, p < 0.001)). Cluster analysis showed that сluster 1 is characterized by a high level of commercialization, whereas сluster 4 demonstrates a high level of innovation activity; cluster 2 has a high level of knowledge intensity and return on science; cluster 3 has a good technological base. The results showed that a high level of financing does not always lead to breakthrough innovation.