Suchergebnisse

Relevance. In Kazakhstan, regional disparities present a major challenge to national development. The COVID-19 pandemic and the recent political turmoil exacerbated this situation because smaller towns and settlements in less accessible regions lack the resources to cope with the consequences of the crisis on their own.Research objective. The study aims to propose a methodological approach to assessing the socio-economic performance of vulnerable and depressed territories.Data and methods. The methodological approach is developed taking into account the specifics and peculiarities of territorial development, as well as the availability of statistical information in small towns and settlements. The depressiveness and vulnerability ranking were compiled for monotowns and small towns in Kazakhstan. The study relies on the statistical data provided by the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan.Results. The proposed methodology was applied to analyze the aggregate indicators characterizing the socio-economic performance of towns and settlements in East Kazakhstan, North Kazakhstan, and Zhambyl regions between 2009 and 2019. The towns of Ridder, Semey, Mamlyutka, Sergeevka, Karatau, and Janatas were classified as severely depressed areas. The same towns and the town of Bulaev demonstrated the highest levels of vulnerability.Conclusions. The research findings may be of interest to government agencies of all levels. The methodology can be used for assessing the socio-economic performance of lagging areas for more informed decision- and policy-making.

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.
AcknowledgmentThis 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.

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).