Nailya Nurlanova

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.

Acknowledgment
This 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).

In recent years, inequality in the economic and social development of regions and population has increased in Kazakhstan. The purpose of this paper is to assess the level of differences between the regions of Kazakhstan in the field of social, economic, innovation, and infrastructural inclusion and offer recommendations for reducing regional inequality. The research hypothesis is that the high level of economic inequality of the regions determines the high level of differences in the field of social inclusion, inclusion in the field of infrastructure and innovation. The assessment of regional differences was carried out according to four groups of economic, social, innovative, and infrastructural indicators; private and integral indices of inclusive development of regions were calculated. The gaps between the highest and lowest index by groups were revealed: social inclusion – 3.37; economic inclusion – 7.45; infrastructure inclusion – 2.96; innovative inclusion – 6.67. A map of inclusive development of the regions of Kazakhstan is developed. Estimates showed that despite the large gap in the economic development of the regions, the gap in social and infrastructural development remained smaller. In cases where the gap between the maximum and minimum values of the index in the regions increased, more and more regions found themselves in the group with a low level of inclusive development.

Acknowledgment
This study is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP09259004 “Priorities and mechanisms of inclusive regional development of Kazakhstan in the context of overcoming the economic recession”).
We would like to thank the anonymous reviewers and issue editors for their helpful comments.

In today’s world, many countries, including Kazakhstan, are facing growing income inequality, poverty, and an increasing polarization of society. These challenges threaten social stability and make it difficult to achieve the Sustainable Development Goals. The purpose of this study is to investigate the size and trends of regional and sectoral wage disparities in Kazakhstan, as well as to create a typology based on the average wage levels in different regions and to provide recommendations for reducing income inequality. The study tested hypotheses about the relationship between the average nominal wage and the level of GRP, level of education, industry specialization, type of ownership, and size of enterprises. The methods of expert survey, correlation, and cluster analysis were used. The study revealed the tendency of increasing inequality of labor income. The largest differences between wages in extractive industries and agriculture were revealed in the Atyrau (11.5) and Mangystau (9.2) regions and Astana (7.2). Differences in average wages between regions were estimated at 1.7 to 7.8 times. The most significant factors affecting the level of average wages are gross regional product per capita and the share of gross value added of the quasi-public sector in the gross regional product. In order to reduce differences in wages, it is recommended to introduce progressive taxation, apply regional increasing coefficients, and calculate the minimum wage based on the hourly wage rate.

Acknowledgment
This work is supported by the Committee of Science Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant BR21882165).