Abstract
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.