The role of education, human capital, and quality of life in regional development: Evidence from Kazakhstan

Type of the article: Research Article AbstractThis study aims to assess the impact of key components of quality of life, including human capital, social accessibility, and industrial development, on effective territorial development management in Kazakhstan. The study uses an index approach, cluster and correlation analysis, and Markov transition models. The empirical dataset covers 17 regions of Kazakhstan over the period 2013–2023 and is based on official annual statistics, including indicators of education (number of students and teaching staff), employment, income, digital infrastructure, and industrial development. The Quality of Life Index (QLI) was calculated using normalized variables, followed by regional grouping and dynamic modeling. Results indicate that the highest QLI values in 2023 were recorded in Astana city (0.837), Mangystau (0.790), and Shymkent city (0.771), where educational coverage and academic staffing are significantly higher than in other regions. Correlation analysis reveals that industrial development (r = 0.493, p = 0.052) and educational potential (ρ = 0.491, p = 0.045) are positively associated with regional upward transitions in quality of life. Cluster analysis identified three stable groups of regions: with active social transformation (e.g., Mangystau, Kyzylorda), balanced growth (Karaganda, Pavlodar), and limited dynamics (Turkistan, East-Kazakhstan). Thus, regions with strong educational infrastructure and dynamic labor markets, such as the Mangystau region, Astana and Shymkent cities, consistently outperform in QLI. In contrast, structurally lagging regions, such as Turkistan and East Kazakhstan, exhibit limited social mobility and weak institutional support. Consequently, investment in human capital is essential for reducing regional disparities and promoting sustainable territorial development. AcknowledgmentsThis research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (“Modernization of the quality assurance system of higher education in Kazakhstan based on digitalization: development of approaches, mechanisms and informationbase” No.BR24992974).

Authors

Institutions

Publication Details

Journal
Problems and Perspectives in Management
Published
2025-08-14
DOI
https://doi.org/10.21511/ppm.23(3).2025.19
Citations
3
Primary Topic
Economic Growth and Productivity
Type
article
Field-Weighted Citation Impact
9.39
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The role of education, human capital, and quality of life in regional development: Evidence from Kazakhstan

Aigul Mukatay, Gaukhar Kenzhegulova, Svetlana Kozhirova, Temirlan Abdykadyr et al.
3 citations
Problems and Perspectives in Management
Economic Growth and Productivity
9.39
article

The role of education, human capital, and quality of life in regional development: Evidence from Kazakhstan

Aigul Mukatay, Gaukhar Kenzhegulova, Svetlana Kozhirova, Temirlan Abdykadyr, Raushan Unerbayeva
article en
3 citations

Abstract

Type of the article: Research Article AbstractThis study aims to assess the impact of key components of quality of life, including human capital, social accessibility, and industrial development, on effective territorial development management in Kazakhstan. The study uses an index approach, cluster and correlation analysis, and Markov transition models. The empirical dataset covers 17 regions of Kazakhstan over the period 2013–2023 and is based on official annual statistics, including indicators of education (number of students and teaching staff), employment, income, digital infrastructure, and industrial development. The Quality of Life Index (QLI) was calculated using normalized variables, followed by regional grouping and dynamic modeling. Results indicate that the highest QLI values in 2023 were recorded in Astana city (0.837), Mangystau (0.790), and Shymkent city (0.771), where educational coverage and academic staffing are significantly higher than in other regions. Correlation analysis reveals that industrial development (r = 0.493, p = 0.052) and educational potential (ρ = 0.491, p = 0.045) are positively associated with regional upward transitions in quality of life. Cluster analysis identified three stable groups of regions: with active social transformation (e.g., Mangystau, Kyzylorda), balanced growth (Karaganda, Pavlodar), and limited dynamics (Turkistan, East-Kazakhstan). Thus, regions with strong educational infrastructure and dynamic labor markets, such as the Mangystau region, Astana and Shymkent cities, consistently outperform in QLI. In contrast, structurally lagging regions, such as Turkistan and East Kazakhstan, exhibit limited social mobility and weak institutional support. Consequently, investment in human capital is essential for reducing regional disparities and promoting sustainable territorial development. AcknowledgmentsThis research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (“Modernization of the quality assurance system of higher education in Kazakhstan based on digitalization: development of approaches, mechanisms and informationbase” No.BR24992974).

Problems and Perspectives in ManagementVol. 23(3)
Hong Kong Baptist University (HK), Al-Farabi Kazakh National University (KZ), University of International Business (KZ), Kazakh-American Free University (KZ), University of Hong Kong (HK)
Industry, innovation and infrastructure
Openalex Percentile: Top 2%
Economic Growth and Productivity
9.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.