Understanding the impact of economic factors on bank lending is crucial in Kazakhstan’s modern economy, characterized by volatile inflation and fluctuations in real wages. This paper aims to investigate the link between bank lending and economic factors such as inflation, real wages, and consumer expenditure in a regional context. Data from the Bureau of National Statistics and the National Bank, covering the period from 2012 to 2022, were used to uncover how economic factors influence bank lending. For the analysis, various economic indicators were integrated through normalization and averaging. Analysis reveals significant regional disparities in real wages and consumer expenditures, which impact the demand for bank credit. The results of the correlation matrix showed that both real wages (P-value < 0.001) and inflation (P-value < 0.001) significantly impact bank lending, with an R² value of 0.998, indicating that the model explains 99.8% of the variation in bank lending. The regression analysis highlights that regions with higher real wages, such as Astana, Almaty, and Atyrau, provide the most favorable conditions for banking sector growth, demonstrated by a strong relationship between wages and bank lending. In contrast, regions with lower wage levels, such as Turkestan and Zhambyl, show a significantly weaker connection (around 0.65), reflecting their lower attractiveness for banking investment and emphasizing the need for policies to address social inequality. The Durbin-Watson test confirmed no autocorrelation in residuals (DW = 1.89), although heteroscedasticity was detected, suggesting the need for further model adjustments. The study emphasizes the importance of developing economic policies that can balance regional development and improve financial stability.

Urbanization process affects global socio-economic development. Originally tied to modernization and industrialization, current urbanization policy is focused on productivity, economic activities, and environmental sustainability. This study examines impact of urbanization in various regions of Kazakhstan, focusing on environmental, social, labor, industrial, and economic indicators. The study aims to assess how different indicators influence urbanization trends in Kazakhstan, particularly regarding environmental emissions and pollution. It delves into regional development patterns and identifies key contributing factors. The research methodology is based on classical economic theories of urbanization and modern interpretations emphasizing sustainability and socio-economic impacts and includes two stages. Shannon entropy measures diversity and uncertainty in urbanization indicators, while cluster analysis identifies regional patterns. Data from 2010 to 2022 for 17 regions forms the basis of analysis. Regions are categorized into groups based on urbanization levels leaders, challenged, stable, and outliers. This classification reveals disparities in urban development and its impacts. Findings stress the importance of integrating environmental and social considerations into urban planning and policies. Targeted interventions based on regional characteristics and urbanization levels are recommended to enhance sustainability and socio-economic outcomes. Tailored urban policies accommodating specific regional needs are crucial. Effective management and policy-making demand a nuanced understanding of these impacts, emphasizing region-specific strategies over a uniform approach.

The purpose of the study was is to assess the impact of key factors (including employment, income, poverty level, prices and social support) on the dynamics of social pressure in Kazakhstan. The analysis covered the period from 2014 to 2024 and utilized official data. The methodology combines entropy-based ranking of indicators, calculation of the Socio-Economic Pressure Index (SEPI), Social Stability Index (SSI), and Social Inertia Index (SII), as well as phase-portrait visualization. The entropy ranking revealed that the share of population below the food basket cost (di = 0.71; Wi = 0.2381) and housing assistance (di = 0.516; Wi = 0.1728) had the highest variability and the strongest influence on SEPI. Moreover, SEPI rose from 0.0967 in 2014 to its peak in 2023 – over 20 times higher – before falling to 0.53 in 2024. SSI dropped from 4.94 in 2017 to 0.44 in 2023, with minimal adaptive capacity, and partial recovery to 1.87 in 2024. There was recorded instability of positive changes and a high likelihood of renewed pressure due to the lowest value of SII (–3.24) in 2024. Thus, long-term stability and a reduction in the social sphere’s susceptibility to external and internal shocks require integrated policy measures that combine targeted support, income regulation, and adaptive governance.