Informal economic activity poses significant challenges to fiscal capacity, regulatory efficiency, and inclusive development across the region. The purpose of this study is to identify and analyze the key factors influencing the level of the informal economy in Central Asia and the Caucasus. The empirical database is based on panel data for six countries (Kazakhstan, Kyrgyzstan, Tajikistan, Azerbaijan, Armenia, and Georgia) compiled from statistics from the World Bank and the IMF. A panel regression model with random effects was applied, taking into account the impact of macroeconomic and institutional variables. The results show that higher GDP per capita significantly reduces the size of the informal economy (coefficient –0.00026, p < 0.001), confirming the inverse relationship between income and the shadow sector. Financial development has a strong negative impact (–13.43, p < 0.001), highlighting the role of infrastructure and digital finance in formalization. Urbanization demonstrates a dual effect: in its early stages, it contributes to the growth of informal employment, but in mature urban systems, it reduces its level (–0.41, p < 0.001). Trade openness, on the contrary, positively correlates with the informal economy (+0.019, p<0.001), which indicates the risks of liberalization without accompanying digitalization of customs procedures. The findings confirm the need for targeted state measures to formalize the economy through digital tax infrastructure, expanded financial inclusion, and simplified business registration procedures. Future research may focus on examining tax distortions and wealth inequality as factors sustaining the informal sector.

Currently, digital technologies are developing rapidly and digitalization is the main direction of transformation of economic processes in all countries of the world.  The oil and gas sector is one of the most capital-intensive and technologically complex areas of activity, but at the same time ensures the sustainable development of companies in conditions of high market volatility and limited natural resources. The purpose of the study is to analyze the features and prospects of digitalization of the oil and gas industry in Uzbekistan using the example of Uzbekneftegaz JSC. The paper uses methods of historical periodization, comparative and systematic analysis, as well as qualitative categorical analysis. The empirical base includes the official data of Uzbekneftegaz JSC for 2021-2024, materials from the National Statistical Committee of Uzbekistan, as well as the results of pilot digital projects in the industry. The results of the study show that in 2021-2024, natural gas production decreased by 17.4% (from 33.9 to 28.0 billion m3), and oil production by 40.7% (from 116.1 to 68 thousand tons), while the production of diesel fuel increased by 53.5% (from 391.9 to 601.4 thousand tons) and aviation kerosene by 60.3% (from 126.7 to 203.1 thousand tons).  The results of the study indicate that the digitalization process in Uzbekneftegaz JSC is taking place in stages, which there is a reduction in manual labor, increased transparency of operations, and increased real-time production accounting. In further research, it is necessary to pay attention to the analysis and proposal of a set of measures to improve legislation, standardize IoT and AI.

The purpose of this study is to develop and substantiate the socio-technical trust architecture (hereinafter – STTA) model, adapted to the national practice of banking audit, drawing on Estonia’s experience and on the theoretical frameworks of socio-technical systems and institutional trust. The research methodology is based on a documentary analysis of Kazakhstan’s regulatory framework, a comparative study of international experiences (in particular, the Estonian X-Road model and KSI blockchain technology), as well as theoretical modelling. The work uses statistical materials from the National Bank of the Republic of Kazakhstan, the Agency for Regulation and Development of the Financial Market (2022-2024), data from international organizations (the World Bank, the OECD), as well as empirical research on the Estonian practice of digital auditing. A four-level STTA model has been developed, comprising the user level (portals for civil audit via NDID), the management level (regulatory sandboxes), the technical level (blockchain audit, API infrastructure), and target trust indicators (Public Verifiability Index, “trust rate” metric). The model assumes an increase in the level of public trust in banking auditing in Kazakhstan to 80% by 2030 (from the current ~38%), a 30% reduction in repeated violations, and a significant decrease in fraudulent transactions. The study highlights the need for regulatory recalibration and IT infrastructure upgrades to build trust through Estonia-inspired mechanisms. The results are practically relevant for transition economies seeking to strengthen digital accountability and citizen engagement in financial oversight.

Today, digital transformation has a significant impact on the structure of trade, consumer behaviour and macroeconomic indicators, especially in developing countries. This study aims to assess the impact of digitalisation on the development of electronic commerce in Kazakhstan and its relationship with macroeconomic indicators, as well as to predict the dynamics of e-commerce using regression and time analysis. The official statistical data of the Bureau of National Statistics of the Republic of Kazakhstan, the National Bank, as well as international organisations (the World Bank, ITU) were used as source data. The research methodology includes descriptive statistics, correlation and multiple regression analysis in SPSS, as well as forecasting the volume of electronic commerce using the ARIMA. The results showed a high correlation between the volume of e-commerce and the level of Internet penetration (r = 0.83), the number of users (r = 0.85), as well as the volume of cross-border trade (r = 0.95). Multiple regression showed that e-commerce in the service sector (β = 0.707, p < 0.001) and the share of e-commerce in the retail structure (β = 0.347, p = 0.003) had the most significant impact. The results of the study emphasise the need to review the marketing strategies of enterprises, develop digital infrastructure and improve government policy in the field of cross-border electronic commerce. In future work, it is advisable to use microdata to include behavioural factors, as well as expand time series and apply nonlinear models, including structural shifts, to analyse the impact of digitalisation on trade more accurately.

In recent decades, there has been an increase in scientific interest in women’s migration, reflecting the globalisation of migration flows and increased gender sensitivity in research. The aim is to explore the mapping of the scientific field devoted to women’s migration through analysis to identify key trends, thematic areas, and international scientific collaborations. The Scopus database covering the period from 1979 to 2025 is used as an empirical base. The sample includes 860 articles selected based on relevant keywords related to women’s migration. Drawing on a dataset of 860 peer-reviewed articles from the Scopus database spanning 1979–2025, the analysis employs advanced bibliometric tools including VOSviewer and Bibliometrix (R package). The study examines publication dynamics, prolific authors and journals, influential countries, citation patterns, and co-occurrence networks of keywords. The results reveal six dominant thematic areas: labour migration, gender discrimination, marital migration, cultural norms, socio-economic mobility, and structural barriers. The findings reveal six dominant thematic clusters: labour migration, gender discrimination, marital migration, cultural norms, socio-economic mobility, and structural barriers. The United States (298 articles), the United Kingdom (170), and Canada (79) emerged as the most productive contributors. While research is primarily concentrated in North America and Europe, academic interest is steadily increasing in Southeast Asia, East Asia, and Latin America. This article will guide future research by providing a scientific map of studies that are at the intersection of migration and gender issues.

Accelerated and uneven demographic growth in Kazakhstan is shaping spatially differentiated demand dynamics for places in early childhood education institutions and first-grade classes, necessitating anticipatory planning. The aim of the study is to analyze the impact of demographic growth on preschool and primary education infrastructure, to forecast the demand for places using the cohort-age method, and to develop targeted recommendations to prevent infrastructure shortages. The study applies an agecohort (cohort-component) projection integrated with Geographic Information Systems (GIS) and business intelligence (BI) visualization to assess regional needs without relying on school “capacity” calculations. In 2029, the number of preschool-age children is expected to increase primarily in the southern and western regions, indicating the need to expand the network of early childhood education providers. By 2030, the highest first-grade intake is projected in Almaty region (approximately 5.8 thousand), Kyzylorda region (approximately 5.4 thousand), and Shymkent city (approximately 5.9 thousand). Regression analysis confirmed the significant impact of fertility (β=0.48; p<0.01) and migration (β=0.31; p<0.05) on the infrastructural load. These estimates provide a foundation for prioritizing and phasing in additional seats, planning workforce needs, targeting the allocation of resources and subsidies, and aligning construction plans with anticipated demographic dynamics, measures that will promote more equitable access to education and strengthen the resilience of regional systems.

The research aims to identify changes in external migration of the working-age population of Almaty in the context of geopolitical instability, starting from 2022. The research methodology is based on a quantitative approach and employs the following analytical methods: descriptive statistics, comparative analysis of key indicators (number of arrivals, emigrants, share of migrants with higher education) before and after 2022, and difference-in-differences. The source database of research is analytical reports from international organisations (UNHCR, IOM, World Bank, OSCE) and official statistics from the Bureau of National Statistics of the Republic of Kazakhstan for 2000–2023, including dynamic tables on external migration by country, age, gender, and education. The findings show that since 2022, Almaty has transitioned from stable emigration to active immigration, primarily of skilled specialists from Russia. In 2023, the influx of migrants exceeded the outflow by 6.5 times, and their total number increased by 194.6% compared to the previous year. For the first time in 24 years, an influx of specialists with higher education was recorded, especially from Russia and the Baltic countries. More than 60% of immigrants had higher or secondary specialized education. The most significant increase was recorded among specialists in technical (27.5%), economic (19.3%) and pedagogical (17.8%) fields. The factors that contributed to this reversal are identified, including regional instability and the attractiveness of Almaty. The application of the results consists of substantiating recommendations for state migration policy: developing mechanisms for integrating skilled migrants, digital monitoring of flows, etc.

The relevance of scientific interest in the problem of population participation in the economic processes of the country is determined by the recognition of the key role of human capital in ensuring the growth of national welfare. The purpose of the article is to substantiate the author’s interpretation of the concept of “population involvement in the economic processes of the country” and to identify its impact on the level of economic well—being of citizens.  The research uses general scientific (analysis, synthesis, generalization) and economic-statistical methods, including correlation analysis, index method and grouping method. Theoretical approaches to determining the essence of economic involvement are systematized, its key components are clarified, and indicators characterizing economic well-being are substantiated.The results showed a stable positive correlation between indicators of economic activity of the population and key indicators of well-being. A comparative analysis showed an increase in the integral index of well-being in most regions of the country: if in 2010 a low level was recorded in 12 of the 16 regions, then by 2023 a high level was reached in three regions (Astana, Almaty, Atyrau region), while noticeable regional disparities remain. The data obtained make it possible to assess the current socio-economic state of society and the effectiveness of government policy in this area. The developed theoretical provisions and methodological approaches can be used in further scientific research, and the collected information base can be used in shaping socio-economic policy at the regional level.

Scientific labour organization is becoming relevant in the context of the rapidly changing requirements of the modern market, especially in the growing human interaction with robotic systems and artificial intelligence. The purpose of this study is to conduct a bibliometric and content analysis of scientific labour organization in agriculture, with a focus on the integration of remote sensing technologies and precision farming. The methodological basis of the work included bibliometric and content analysis of scientific articles selected from the Web of Science database for the period 1992-2025, using clusterization (CiteSpace 6.3.R1). The results showed a steady increase in publication activity: since 2017, the number of papers has increased to four  per year, and the peak of citations occurred in 2022. Cluster analysis revealed two dominant areas: “Industry 4.0” (77 articles, the average publication year is 2016, S = 0.99) and “Precision Agriculture” (34 articles, the average year is 2014, S = 1.0). These clusters have shown that sustainable land use technologies and precision farming innovations are changing the organization of labor and management of agricultural enterprises. The results demonstrate the growing interest in the problems of labor organization in the context of the digitalization of the agricultural sector, the strengthening of interdisciplinary ties and the expansion of the range of applied research. In the future, it is advisable to expand databases for analysis, include more intersectoral research and develop organizational models that take into account the social and ethical aspects of the introduction of new technologies.

The agricultural sector plays a key role in ensuring economic stability and food security, but the factors determining farm profitability remain a matter of debate. The purpose of the study is to assess the impact of subsidies, farm size and age on the annual income of agricultural enterprises in the North Kazakhstan region. Panel data from 456 farms for 2010-2023 (6354 observations) was used as a database. Methodologically, the work is based on multifactorial regression using a random effects (REM) model and stable standard errors. Using balanced panel data from 2010 to 2023, a multiple regression model with robust standard errors was applied. The results show that the size of the farm has the most significant and statistically significant positive impact on income (𝛽=1,278, p < 0.001), confirming the existence of economies of scale. The impact of subsidies (𝛽= − 0.143, p = 0.789) and farm age (𝛽 = 0.050, p = 0.305) turned out to be statistically insignificant. The results indicate the need to reorient agricultural policy to support effective farm consolidation, improve subsidy allocation mechanisms, and develop targeted programs to help young farmers. Furthermore, the application of the robust standard errors technique, which is rarely used in prior domestic studies, strengthens the methodological reliability of the results. Based on the findings, several policy recommendations are proposed: subsidies should be redirected toward enhancing productivity and innovation, supporting large and efficient farms, and improving financial and institutional mechanisms for young farmers.