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The article examines the unique characteristics of spatial spillover effects in the Russian economy and their connection to the level of economic activity and its variability across regions. The study employs methods based on Markov chain theory with discrete time and continuous state space to analyze the spatial dynamics of regional indicators. The findings reveal that not only a commonly low level of economic activity but also significant disparities in its levels between regions hinder the emergence of positive spatial externalities. Regions that lag considerably behind their neighbors do not experience accelerated growth; instead, they fall even further behind both their neighbors and the national average. Conversely, regions with smaller differences in economic activity levels and those with above-average economic activity are more likely to experience positive spatial spillover effects. This leads to a convergence in economic activity levels and results in positive spatial autocorrelation across regions. In such cases, regions catching up with their neighbors benefit from the greatest acceleration in development, while leading regions tend to slow down slightly. Thus, spatial autocorrelation, which reflects the degree of similarity among neighboring regions, can both result from and reinforce the processes of spatial concentration or dispersion of economic activity.

In the current geopolitical climate, with heightened risks and threats related to foreign economic activity, the importance of understanding tax revenue sources, their regional distribution, and sectoral diversification has increased significantly. Along with economic development, the movement of revenues to the budget system is influenced by the level of the tax burden. This study aims to assess the evolution of tax revenues and identify the factors driving their dynamics and changes in sectoral and territorial structures, as administered by the Federal Tax Service. The analysis reveals that from 2010 to 2022, the growth rate of Russia’s gross regional product (GRP), even when measured in current prices, steadily declined until 2020. Tax revenue trends closely mirrored this economic performance. A sharp decline in budget system resources was averted after 2018 due to a marked increase in the tax burden. Of all the growth in the budget system’s revenue, 10% was attributed to the increased tax burden, while GRP dynamics drove 90%. Significant structural shifts that shape the scale and trajectory of the country’s budget revenues are concentrated in a relatively small group of regions. About a quarter of the regions with the highest share of total revenues account for around 80% of Federal Tax Service revenues (on average from 2010 to 2022). Sectors such as trade and certain manufacturing sub-sectors typically demonstrate a higher-than-average return on sales and relatively low tax burden assessments. These sectors, therefore, warrant closer scrutiny to explore opportunities for increasing tax revenue in both the short and medium term.

This article addresses the insufficient scientific attention given to the impact of public and private infrastructure investments on reducing regional inequalities, especially within the BRICS countries, and particularly Russia. Despite the importance of this issue, it has been under-researched there, unlike in other countries such as China. To bridge this gap, the article evaluates how infrastructural financialization influences uneven regional development in Russia. Using a Tobit regression model and panel data from 2005 to 2019, the study analyzes regional development disparities, with infrastructural finanicate that advanced infrastructural financialization contributes to reducing regional inequality in Russia. Although Russia’s economy focuses on public administration, the article emphasizes the need for increased regionally proportional private investment in infrastructure to achieve regional convergence. Notably, the study’s conclusions differ from those of studies using similar methodology abroad, highlighting the controversial nature of the topic.

The article considers the structural and institutional factors that have determined the levels and dynamics of macroeconomic indicators in the Siberian Federal District (SFD) over the past 20 years. A trend of peripheralization is revealed, manifested in the fact that most of the district’s socio-economic indicators lag behind the national average. We highlight the reasons behind changes in the structure of economic activity and income, as recorded by official statistics, which have led to income concentration in capital regions. At the same time, non-capital regions show reduced formal participation in overall outcomes. The resulting gap between the actual distribution of productive forces and the macroeconomic indicators reflects an inter-regional redistribution of financial resources, contributing to strong disparities in living standards. The article also underscores the role of sectoral restructuring in the SFD’s lagging labor productivity. Lastly, the opportunities and limitations for economic growth in the district, in relation to labor and investment resources, are analyzed.

This article presents an assessment of the regional economic specialization, using the Republic of Bashkortostan and its manufacturing industry as a case study, analyzed in relation to public finance performance in this constituent entity of the Russian Federation. The TOPSIS method was employed as a tool to identify the most promising economic activities for financial support, aiming to enhance the performance of public finance utilization in the region. The study has found that in 2021-2022, amid the impacts of COVID-19 and sanctions on the regional economy, the significance of the public finance indicator (revenue collected per employee in the region) increased in the evaluation of economic specialization. What is more, despite a shift in the preferred area of support from the woodworking industry (2019-2020) to pharmaceutical production (2021-2022), the core of the region’s economic specialization remained virtually unchanged. Priority industries for continued financial support include chemical production, vehicle manufacturing, paper production, electrical equipment manufacturing, and non-metallic mineral products. Supporting these sectors is expected to maximize the performance of public finance use in the Republic of Bashkortostan’s manufacturing industry.

This article, building on theories that explore the causes and factors of company growth, focuses on identifying growing companies as a key element in developing high-tech businesses. It presents a methodology for categorizing companies that influence regional market dynamics, where the regional market is defined as the set of companies within a specific region. The categorization is based on company size (four levels) and age (four levels), grouping companies from each region into 16 distinct size and age categories. This methodology is tested against high-tech business development in Russia’s eastern regions. Despite regional variations in the revenue structure of high-tech businesses, large mature companies are found to dominate across all regions. Analyzing the contribution of different size and age groups to overall regional revenue growth reveals the groups driving growth in each region. Targeted state support for these key groups could have a more significant impact on regional economic development. The proposed methodology can also be applied to assess growth dynamics in other industries and regions.

This study explores internal resources for territorial development based on human capital by identifying a sector of the regional economy associated with the economic activities of the local population. We use the concept of “embeddedness" of economic actions within the regional community to describe this sector. The share of income derived from entrepreneurship and property among the local population is proposed as a criterion for measuring economic embeddedness, reflecting the extent to which the regional community participates in market relations as an economic actor. The analysis highlights spatial differences in the degree of economic embeddedness, notably in Siberian resource regions where external corporations dominate the economy through raw material extraction and primary processing. The development of the embedded sector, especially in areas related to intellectual activity, plays a part in retaining the most active and educated members of the population in eastern regions. The findings can be applied to regional socio-economic planning, advocating a shift from reliance on natural resources to prioritizing human potential by fostering the growth of the embedded economy.

This study aims to examine the peculiarities of the manufacturing industry’s development in the eastern regions of Russia. Can the “eastern vector" of regional development be considered a noteworthy factor in this dynamic? We investigate several aspects of economic processes in the eastern regions during the economic shocks of2020-2021 and 2022-2023, including the dynamics of production, labor productivity in manufacturing, and tax revenues from manufacturing industries. The calculations are based on the production index. In terms of production volumes, industrialization in the east of the Russian Federation generally outpaced the national average from 2017 to 2023, with the exception of2022, though results varied significantly by region. Labor productivity in all Far Eastern regions was higher in 2022 than in 2017. However, according to the foreign economic activity (FEA) data for “Manufacturing Industries" in the Russian East, this indicator was below the national average in 2022, and in four regions, it declined compared to 2017. Given the current limited availability of labor resources, this poses risks to the continued growth of the manufacturing sector in the eastern regions. An analysis of Federal Tax Service data revealed a substantial increase in tax revenues from the manufacturing industry both nationally and in the eastern regions in 2023. While this trend is positive for overall budget revenues, it also suggests a growing tax burden on the industry, which could negatively affect its development and modernization in the medium term. The findings support expanding the argument for a “pivot to the east." Rather than focusing solely on increasing exports, the priority should be on fostering horizontal economic relationships and cooperation between regions in Russia’s Asian part to improve the efficiency of regional economic systems. That is to say, a “pivot to the east" should first and foremost be a “pivot to the East of Russia".

This article examines the social determinants of urban community consolidation. Its goal is to test hypotheses regarding the relationship between long-term socio-economic and socio-demographic trends in urban communities within Russia’s border regions and the population’s perception of social consolidation. By comparing statistical data and sociological research findings, the authors demonstrate that attitudes toward consolidation are not necessarily tied to favorable demographic indicators. Migration has a mixed impact on the prevalence of consolidation in the public consciousness (when cultural distance is significant, consolidation tendencies strengthen among natives as a protective response, whereas smaller cultural distances do not encourage solidarization). The study finds that the “upper" and “lower" strata of the urban population are most inclined toward consolidation, while the “middle" class remains relatively passive. Paradoxically, the erosion of the middle class fosters stronger consolidation attitudes. Additionally, the population’s awareness of the presence of consolidation infrastructure in their city (such as NGOs and public associations) and participation in these organizations contribute to the development and spread of consolidation efforts.

The distribution of woody plants of the Kemerovo region according to the scheme of floristic zoning of Kuzbass is given. The characteristic features of forest communities for each floral area are noted. It was found that woody plants in Kuzbass are represented by 173 species, 69 genera and 29 families. The dendroflora of Kuzbass consists of 94.8 % of flowering plants, the share of gymnosperms accounts for 5.2 %. The largest families of woody plants of the Kemerovo region are: Rosaceae, Salicaceae, Ericaceae, Betulaceae, Grossulariaceae, Lamiaceae and largest genera: willows ( Salix L.) and poplar ( Populus L.). Updated data on floristic areas show that the first place in terms of the number of native and introduced species is occupied by the most densely populated area - the Kuznetsk Basin. In second place in terms of the number of species is the Kuznetsky Alatau floristic district with minimal participation of introduced species. In total, 56 alien woody plants were found in the flora of Kuzbass. Of these, there are 19 advent trees, 3 of which are found in all floral areas. Of the 37 cultivated species, 12 are found in all floristic areas. As part of the flora of woody plants of the Kemerovo region, 10 species are included in the «Red Book of Kuzbass» (2021). For the narrow endemic of Kuzbass, Dracocephalum krylovii Lipsky, it is proposed to change the rarity category of the species from 2 to 1. Six species included in the «Black Book of Flora of Siberia» (2016) were noted, indicating the status of invasiveness of each. It is proposed to establish the status of invasiveness for Ulmus laevis Pall. 4 and include it in the list of Black Book Hippophae rhamnoides L. with status 4. According to generally accepted classifications of life forms, it was found that summer-green shrubs and phanerophytes predominate in the composition of the dendroflora of Kuzbass.