In the current social conditions, the problems of inequality associated with the uneven distribution of income in society is an important research problem. Thus, it is necessary to investigate the level of regional differences in income distribution in developing countries like Kazakhstan. The study aims to assess the influence of income, social expenditures, and inequality in the distribution of education and education costs between different regions of Kazakhstan. Unlike previous scientific papers in this area, this paper uses panel data on the distribution of human capital and income in 17 regions of Kazakhstan. The methodological framework of the research is represented by methods of statistical assessment of economic inequality, such as the indicator of differentiation, reflecting the degree of social and economic inequality. Based on the proposed methodology, we analysed the disparity in the level of education and obtained data on the standard deviations of the distribution of education for the population of the regions of Kazakhstan. According to these data, inequality changes over time and affects the distribution of education and education costs between different areas. Income inequality is slightly higher in Karaganda and East-Kazakhstan regions; other areas have a more equitable income distribution by about 0.05 Gini coefficients. The regression specification shows that large megacities like Shymkent, Almaty, and Astana have a more significant influence, while Mangystau and North-Kazakhstan regions have minor power. The obtained results emphasise the importance ensuring access to education for reducing regional disparities and achieving stability in income distribution.

The study aims to analyze the innovation potential of enterprises, explain the use of the binary regression methodology, and explore different indicators of the enterprises in the regions of Kazakhstan for building an effective management strategy. Methodological substantiation is based on the complex survey data analysis, provided by the World Bank Enterprises Survey (WBES) for Kazakhstan. WBES database has covered a sociological survey of enterprises, which was conducted using a random survey and representativeness among 1,296 enterprises, mainly in the production sector. Besides, the data were collected among companies regarding their experience in environmental perception (including innovation activity), in which they worked. The results have demonstrated that the age of the company, exporter status, type, sector, or activity – all these have a positive influence on the company’s tendency to innovations. However, as part of the study, it has found out that competitors in the marketplace and regions of activity of enterprises predominantly negatively affect the prospects of introducing innovation. It was also in evidence that the same factors (foreign ownership, advanced training, type, size, and sector of an enterprise) are essential determinants of product, technology, R&D, ICT, and innovation. Obtained results can be used by enterprises for building an effective management strategy of own business innovative development, as well as by local authorities to upgrade the competitive performance. AcknowledgmentsThis study has been funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (Grant “Priorities and mechanisms of inclusive regional development of Kazakhstan in the context of overcoming the economic recession” No. AP09259004).

The study examines Kazakhstan's agricultural sector and its potential for developing resilient agro-hubs, focusing on identifying regions that can contribute to the country's long-term agricultural growth. The purpose of this study is to examine essential agricultural indicators, including gross agrarian output, gross crop production, gross livestock production, and agricultural services, in order to identify regions with the potential for agro-hub development. The methodology includes Pearson correlation analysis of data collected from national agricultural reports and regional statistical databases. Data for the study were gathered from national agricultural reports and regional statistical databases, which provide quantitative measures of agricultural output, crop yields, livestock production, and farming services. Results indicate the strongest correlations between Kostanay and North Kazakhstan (0.995 for Gross Agricultural Output and 0.996 for Crop Production, p < 0.001). Additionally, significant alignment in crop production was observed between Almaty and South Kazakhstan (0.969, p = 0.007), whereas weaknesses in agricultural services were noted, particularly in Kyzylorda and Zhambyl, with a negative correlation. The results highlight the northern and southern regions' potential for forming agro-hubs supported by solid production indicators. The study provides strategic recommendations for policymakers to foster regional collaboration, enhance productivity, and promote sustainable agricultural development across Kazakhstan. Future research will focus on improving infrastructure and developing collaborative agricultural initiatives within agro-hubs to strengthen Kazakhstan's agricultural sector resilience.

This paper examines the impact of banking digitization on the development of the banking industry, particularly on banking performance. This study aims to identify critical factors for the development of financial banks and factors for the development of banking digitization in the banking sector of Kazakhstan. Based on this purpose, the core of banking digitization and its definition will be examined. The study conducted a comprehensive analysis that provided quantitative and qualitative characteristics of the development of digital technology and its impact on the development of the banking industry. The problems set out in this paper are solved using quantitative and financial analysis methods. The point index method was used during the study. Data from Halyk Bank’s annual reports from 2019 to 2023 were used to assess digitalization's penetration into the banking industry. A panel approach is also used, allowing for data analysis for individual banks. Our research concludes that bank digitalization clearly impacts bank performance, focusing on the number of digital banking users, digital banking transactions, and IT investment growth on bank performance (such as return on equity, RoAE). The research findings provide implications for the practice of digital transformation of banks, especially in terms of digital investment and performance improvement. This study lays a foundation for future research on the impact of digital transformation on bank performance and provides a reference for investment decisions in the Kazakhstan banking industry.

This study aims to analyze the level of differences based on effectiveness, statistical dependence, and mutual influence of economic indicators for ranking the regions of Kazakhstan. In the paper, a systematic algorithm of actions is used, ensuring the interconnectedness, the sequence of work, and the validity of the methods used. Several model specifications were formulated to identify interregional differences in economic development indicators: the operating data environment analysis model (DEA) and the random effects regression model (RE). The information database of the Bureau of National Statistics of the Republic of Kazakhstan for 2010–2020 was used. The construction of the RE model was carried out in the SPSS program. A regression model with fixed and random effects in panel data was employed to determine the impact of the selected indicators on gross regional product produced (GRP). Based on the results, the influence of the physical volume of industrial products on GRP per capita in the regions of Kazakhstan for 11 years was revealed in both models with a high significance of coefficients. The study results can be used by public administration bodies that carry out effective strategic management by smoothing interregional differences. Moreover, they can determine the prospects for studying other parameters based on efficiency, statistical dependence, and mutual influence of economic indicators for ranking regions. AcknowledgmentThis study has been funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (grant “Priorities and mechanisms of inclusive regional development of Kazakhstan in the context of overcoming the economic recession” AP09259004).

Gender equality in the workforce remains a pressing issue globally, with significant wage gaps and unequal employment opportunities continuing to affect women. This study examines the impact of different occupational categories on women's wages and employment conditions in Kazakhstan. This study used multivariate analysis and regression modelling to study the influence of various professional categories. The study used data on the employment and wages of women in Kazakhstan collected from various annual sources. The results indicate that occupational categories significantly influence wage levels and employment conditions, revealing disparities across professional groups. Multivariate analysis shows that managerial and technical roles have the highest impact, with positive coefficients indicating higher wages and better job stability compared to other roles. In contrast, service workers and administrative employees show weaker impacts, with coefficients around -55,309 and 121,118, respectively, failing to achieve statistical significance (p-values > 0.05). The findings emphasize the critical role of managerial and technical occupations in improving women’s wages and economic outcomes. Structural barriers limit women’s access to high-paying roles, leading to significant wage disparities in service and lower-skilled sectors. Further studies should explore additional variables such as education, regional disparities, and socio-economic factors to understand wage determinants for women in Kazakhstan better.