Makpal Bekturganova

This paper aims to analyze various indicators to explain the impact of inequality and income on economic growth at the regional level of Kazakhstan. The data collected from the Bureau of National Statistics from 1995 to 2020 examined the impact of country, interregional, and market inequality indices and real income/wage on the GRP of different regions. Applying the methods such as analysis of unique statistical data covering 16 regions of Kazakhstan and log-linear multivariate regression analysis, which was carried out using the STATA software package, evidence was provided on the influence of interregional, country inequality, and income on economic growth. The analysis showed the differential impact of inequality and income. It was found at the first stage that the gap between interregional inequality and country inequality is insignificant. It was identified at the second stage that in models with real incomes, an increase in income has a negative impact on the development of the economy of Kazakhstan. All the models obtained are consistent and have (although not very high) significant explanatory power and confirm the relationship between inequality and economic growth. The findings can help policymakers, regionalists, economists, and governmental bodies understand the importance of income inequality and which areas can contribute to the formation of effective regional policy.

Acknowledgments
The study was carried out within the framework of program targeted IRN OR11465433 funding by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan “Development of the concept and mechanisms of balanced territorial development of the economy and society of Kazakhstan”.

This study aims to analyze the impact of logistics and information and communication technologies (ICT) on Kazakhstan’s economic growth, which requires rethinking search and management tools. The study used the methods of descriptive data statistics, checking the data for the normality of the distribution, and Spearman’s correlation analysis. The information database comprised the National Bank, the World Development Bank, and the national statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. The paper determined the dynamics of GDP per capita and logistics, including export and import, for 2005–2020. The construction of the correlation model was carried out in SPSS. Interestingly, the most significant negative relationship was revealed between database-related services and the population and the volume of communication services (.761*).
On the other hand, the results show a positive impact of ICT’s strong relationship with Kazakhstan’s logistics system. A close relationship was revealed between the volume of postal and courier activities and GDP per capita (.946*), and foreign trade turnover and exports and imports (.897*). Furthermore, the correlation analysis showed that the cost of investments in developing data processing services decreases with an increase in GDP and the volume of communication services. The findings of this study are relevant for governmental bodies operating in the field of logistics and transportation. Moreover, they are valuable for the digitalization of existing and designing new logistics systems as a factor in the development of the economy.

Acknowledgment
The study was carried out within the framework of grant funding IRN AP14869297 by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan “Priorities and mechanisms against rural women of Kazakhstan unequal access to the resources”.

This study aims to examine the relationship between higher education and economic development determinants in Kazakhstan’s regions. The paper used two sets of indicators of three-time series: 2010, 2015, and 2020. The analysis constructed a correlation using a panel dataset for 15 regions of Kazakhstan compiled by the Statistics Bureau of Kazakhstan and the National Bank. The first set reflects the determinants of higher education (number of students in colleges and universities, number of teaching staff, and the existing ICT infrastructure in universities). The second set includes indicators of regional economic development (GRP per capita and the population’s income level). The results showed a causal relationship between economic development and the determinants of higher education in the regions of Kazakhstan, which depend on the period. Surprisingly, the number of university students has almost no effect on GRP per capita and the population’s income level. For 2015–2020, the study observed the emergence and strengthening of correlations between economic growth and the development of innovations in universities. The findings also identified Mangystau, Atyrau, North Kazakhstan, and Pavlodar as regions with low innovation development in education. Therefore, the country’s higher education development policy should encourage and strengthen knowledge management systems in these regions. The study concludes that higher education and economic indicators significantly influence the growth of the economy in Kazakhstan.

Acknowledgment
The study was carried out within the framework of program-targeted IRN BR18574240 funding by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan “Development Strategy of Kazakhstan Regional Potential: Assessment of Socio-Cultural and Economic Potentials, Roadmap, Models and Scenarios Planning”.

In the current social conditions, pension systems have become the most important topic on the agenda for many countries. Therefore, governments have started paying attention and should reform their pension systems to guarantee an adequate contribution to pensions. Thus, this study analyzes the impact of investments and social factors on pension savings using Kazakhstan as an example. The paper is based on secondary data from the annual reports of the Unified Accumulative Pension Fund and annual statistical reports of the Bureau of National Statistics of the Republic of Kazakhstan from 2014 to 2022. SPSS software was used to analyze the collected data, specifically through correlation and regression analysis, to determine the impact and relationships between selected indicators (i.e., inflation rate, number of contributors, pension contribution, investment income and average wage). To check the reliability of the models, Fisher’s F-test and Student’s t-test were conducted. Therefore, a VIF diagnosis was conducted. The correlation analysis results showed that in the group of investment factors, pension savings are more dependent on pension contributions (,900**), and in social factors, on average wages (1,000**). Based on the results obtained, all factors have a positive impact on pension savings, except inflation. Inflation growth by 1% on average reduces the amount of pension savings by 23% over the nine-year period between 2014 to 2022, which is reflected in the results of Model 2. The study’s results can be applied to managing pension funds and reforms related to the pension system.

Acknowledgments
This research was funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant “Exploring the impact of economic, social, and environmental factors on the relationship between urbanization and greenhouse gas emissions” No. AP19576071).