A cluster approach to evaluating investment support across economic sectors in Kazakhstan

Research purpose. This study applies cluster analysis methods to identify homogeneous groups of economic sectors in Kazakhstan according to their level of investment support.

Methodology. To examine sectoral investment patterns, cluster analysis was conducted by grouping economic sectors based on indicators of investment activity. The K-means clustering algorithm was employed to classify the sectors into three distinct clusters. The analysis was carried out in a two-dimensional space using principal component analysis (PCA) with the first and second principal components serving as the axes. 

Originality/Value of the Research. The findings provide a foundation for refining investment policy by aligning support measures with the specific needs and capacities of different sector clusters.

Findings. As a result of the cluster analysis, three group of sectors were identified, each internally homogeneous in term of the analyzed set of investment activity indicators. Cluster 0 primarily includes infrastructure-related industries characterized by high capital intensity and relatively low economic returns. Cluster 1 includes sectors that demonstrate high returns on investment but face capital shortages. Cluster 2 comprises the mining industry, which accounts for a significant share of investments and makes a substantial contribution to the country’s economic development. 

1. “Macroeconomic report for 2024 and forecasts” (2025), Halykfinance, available at: https://halykfinance.kz/download/files/analytics/macro2024_.pdf (accessed: June 25, 2025).

2. “Concept of investment policy of the Republic of Kazakhstan until 2029” (2024), available at: https://adilet.zan.kz/rus/docs/P2400000868 (accessed: June 27, 2025).

3. “National Development Plan of the Republic of Kazakhstan until 2029” (2024), available at: https://adilet.zan.kz/rus/docs/U2400000611#z732 (accessed: June 29, 2025)

4. Petrovskaja, M. (2024), “Sovremennoe sostojanie investicionnoj politiki Respubliki Kazahstan”, Economic series of the Bulletin of ENU named after L.N. Gumilyov, Vol. 1, pp. 256–270. DOI: 10.32523/27894320-2024-1-256-270. (In Russian).

5. Sokira, T.S., Belgibaeva Zh.Zh., Smagulova G.S., Belgibaev A.A. (2023). Faktory investicionnoj privlekatel'nosti Vostochno-Kazahstanskoj oblasti, KazNU Bulletin. Economic Series, 145(3), pp. 94-102. DOI: 10.26577/be.2023.v145.i3.09. (In Russian).

6. Belgibaev, A., Pralieva, S. (2024). Analiz vzaimosvjazi mezhdu investicijami v osnovnoj kapital i VRPv zapadnom regione Kazahstana, Economic series of the Bulletin of ENU named after L.N. Gumilyov, (3), 279–295. DOI: 10.32523/2789-4320-2024-3-279-295. (In Russian).

7. Imashev, Je., Utebalieva, B. (2024). Territorial'naja differenciacija investicionnoj privlekatel'nosti promyshlennosti Aktjubinskoj oblasti, Economic series of the Bulletin of ENU named after L.N. Gumilyov, (3), 57–79. DOI: 10.32523/2789-4320-2024-3-57-79. (In Russian).

8. Shin, E.P., Musabaev T.T., Zholamanova M.T. (2024). Vlijanie investicij na konkurentosposobnost' obrabatyvajushhej promyshlennosti (na primere Karagandinskoj oblasti). Central Asian Economic Review. 1. 154-164. DOI: 10.52821/2789-4401-2024-1-154-164. (In Russian).

9. Vertakova, Yulia, Klevtsova Maria, Zadimidchenko Anna. (2022). Multiplicative Methodology for Assessing Investment Attractiveness and Risk for Industries. Journal of risk and financial management, 15, 10, Retrieved from: DOI: 10.3390/jrfm15100419.

10. Zhakupova, M.M. (2024). Sravnitel'nyj analiz investicionnoj aktivnosti v Kazahstane i sosednih stranah: tendencii, problemy, perspektivy, Economic Review of the National Bank of the Republic of Kazakhstan, №3. С.31-54. (In Russian).

11. Al-Banna, Adnan, Yaqot Mohamed, Menezes Brenno C. (2024), “Investment strategies in Industry 4.0 for enhanced supply chain resilience: an empirical analysis”, Cogent business & management, Vol. 11, No. 1. DOI: 10.1080/23311975.2023.2298187.

12. Muazu, Ibrahim, Paul Alagidede. (2018), “Effect of financial development on economic growth in Sub-Saharan Africa”, Journal of Policy Modeling, Vol. 40, No.6, pp. 1104-1125. DOI: 10.1016/j.jpolmod.2018.08.001.

13. Baculakova, K. (2018), “Cluster Analysis of Creative Industries in the Regions and Districts of Slovakia”, Theoretical and Empirical Researches in Urban Management. 3, 74-89.

14. Reiff, M., Ivanicova Z., Surmanova K. (2018), “Cluster analysis of selected world development indicators in the field of agriculture and the food industry in the European Union countries”, Agric. Econ. – Czech, Vol.64, No.5, pp.197-205. DOI: 10.17221/198/2016-AGRICECON.

15. Nuo, Liao & Yong He (2018), “Exploring the effects of influencing factors on energy in industrial sector using cluster analysis and panel regression model”, Energy, Vol.158, pp.782-795. DOI: 10.1016/j.energy.2018.06.049.

16. Darma, Putra, E., & Yuli Pratiwi, M. (2019), “Identification of Leading Sector and Cluster Analysis of Regencies in Kalimantan”, Economics Development Analysis Journal, Vol.8, No.2, pp.224-243. DOI: 10.15294/edaj.v8i2.27237.

17. Bagnara, M. & Goodarzi M. (2023), “Clustering-based sector investing”, SAFE Working Paper, No.397, available at: https://www.econstor.eu/handle/10419/273735 (accessed: June 22, 2025).

18. Hejduková, P., Kureková, L., & Krechovská, M. (2020), “The Measurement of Industry 4.0: an Empirical Cluster Analysis for EU Countries”, International Journal of Economic Sciences, Vol.9, No.1, pp.121134. DOI: 10.20472/ES.2020.9.1.007.

19. Investments in fixed assets (2025), Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan, available at: https://stat.gov.kz/ru/industries/business-statistics/ stat-invest/ (accessed: June 15, 2025).