R-ECONOMY

Relevance. Intergovernmental budgetary regulation is pivotal for promoting territorial equalization and bridging socio-economic gaps among regions. It ensures equitable access to public goods for all citizens, irrespective of their location. The effective distribution of federal financial assistance, guided by the principles of budget federalism, is essential for maintaining macroeconomic stability and fostering sustainable socio-economic development on the national and regional levels. Research Objective. The study aims to assess the competitive positions of Russian regions within the distribution system of federal intergovernmental transfers. Method and Data. To investigate Russia’s system of intergovernmental transfers, the research employs statistical methods, including structural-dynamic, grouping, and graphical analysis, along with novel analytical tools like the dependence coefficient and income coefficient. The study encompasses data from 2015 to 2022, sourced from the Federal Treasury and Federal State Statistics Service (Rosstat). Results. The study analyzes the dynamics of transfers from the federal budget to regional budgets and shows significant transformations in the transfer structure, revealing a decrease in non-targeted transfers and an increase in targeted ones. The study also examines the differences between regions in the distribution of these transfers. Russian regions were grouped depending on the share of federal transfers in their total budget income and the average per capita income in their consolidated budget. The study introduces a novel methodological approach through the use of newly developed tools - the dependence coefficient and income coefficient - to evaluate regional competitiveness. Conclusion. Despite an overall increase in federal transfers, persistent regional disparities intensify competition for financial assistance. These findings can be of interest to policymakers at federal and regional levels, researchers, and educators in relevant fields.

Relevance. In the current economic climate, maintaining the integrity of regional economic space is crucial. This involves ensuring uniform socio-economic development across regions and promoting a high rate of technology transfer from the center to the periphery. Therefore, it is essential to identify sustainable points of spatial development that represent centers of power concentration and guide spatial transformation. Research objective. The study aims to assess the connectivity of the region’s economic space by measuring population mobility. This approach will help identify the centers of social and labor communications that represent sustainable points of spatial development. The focus of the study is on the municipal districts of Sverdlovsk region, which are key elements of its economic space. Data and methods. The study employed geoinformation analysis of origin-destination matrix of population flows in Sverdlovsk region (Russian Federation), provided by Russian mobile operators. Results. The paper presents the analysis of intracity and intercity population flows based on the average daily data of mobile operators for 2022. The intensity and diversification of population flows in the region’s municipal districts, reflecting the connectivity of its economic space, were estimated using geographic information systems and the Python programming language. The study revealed that Sverdlovsk region has a bicentric system of spatial interconnections, with two distinct centers of attraction: Ekaterinburg and Nizhny Tagil, with Ekaterinburg being the dominant center. Conclusions. The proposed classification of municipal districts by the level of their inclusion into the economic space of Sverdlovsk region illustrates that only 5% are characterized by intensive and diversified inter-territorial interaction, while 34% are characterized by low indicators of intensity and diversification of mobile population flows. The spatial structure of the municipalities in Sverdlovsk region, which are located in the zone of attraction to the agglomeration centers, will be maintained and reinforced.

Relevance. Fostering well-being ranks high on regional social policy agendas. With the dynamic shifts in the international economic landscape, known as geo-economic fragmentation, there’s a pressing urgency for stakeholders to optimize resource allocation at the regional level, increasing interest in efficient strategies to adapt to sanctions while enhancing overall well-being. Research objective. This article aims to investigate the dimensions and determinants of the eco- and human capital efficiency in Russian regions in the context of geo-economic fragmentation and sanctions pressure. Data and methods. A proposed three-stage approach integrates factor analysis to identify subjective well-being indicators, data envelopment analysis (DEA) to evaluate socio-eco-efficiency, and panel tobit regression to examine the determinants of efficiency. Microdata from the Rossat Comprehensive Observation of Living Conditions database were utilized, covering the period from 2014 to 2022. To assess efficiency, a DEA model is employed. The output indicators from this model were the estimated measures of subjective well-being. These indicators were validated through factor analysis and included professional satisfaction, safety assessment, accessibility and quality of social and cultural infrastructure in the regions. Results. In the given period, people reported feeling increasingly satisfied with jobs and quality of life, though there was a noticeable slowdown in the growth of human capital development indicators, environmental investments, and real income by early 2023. Efficiency varied significantly among the regions. Industrially developed mining areas and republics in the North Caucasus consistently showed high socio-eco-efficiency, despite limited resources. The efficiency benefited both from digitalization and increased per capita gross regional product, but urbanization had a negative impact. Conclusions. Amid geo-economic fragmentation, regional communities and job markets face significant challenges in adaptation. With the looming risk of declining satisfaction and perceived quality of life, it is imperative for regional policies to bolster tangible well-being indicators and invest in social capital and infrastructure to address these issues effectively.

Relevance. Ensuring equal access to resources is crucial for social development, especially in rural areas. Women in these regions face distinct challenges due to traditional lifestyles and cultural norms, impacting their access to education, healthcare, and economic opportunities. Addressing these challenges is vital for the overall development of rural communities. Research objective. This study aims to develop methodological approaches to assessing women’s access to resources in rural areas of Kazakhstan. Data and methods. Based on the investigation of methodological approaches, multinomial logistic regression analysis was proposed to assess the impact of regional differences on gender gaps in access to various resources. The study is based on qualitative data collected from May to June 2023 from a sociological survey conducted among women aged 18-60 in rural settlements of Kazakhstan. A total of 600 respondents were interviewed, and 542 of the respondents had completed questionnaires. This methodology enables the collection, analysis, and processing of primary data, aiding in the assessment of gender disparities in resource access. Results. The proposed methodology facilitated a thorough analysis of qualitative data, offering insights into the problem of gender disparities. Most respondents rated their access to social and economic resources as average, suggesting that while there are available resources, they might not fully meet rural women’s needs or expectations in terms of level or quality. Conclusions. Regions like Akmola, Atyrau, Mangystau, North Kazakhstan, Turkestan, and Zhambyl show significant disparities in resource access, indicating regional inequalities. Addressing this gap necessitates collaborative efforts between government and businesses to enhance resource availability and broaden opportunities for rural women.

Relevance. In the pursuit of sustainable development, the circular economy takes precedence as a fundamental imperative for industrial transformation. The current trend in the development of the circular economy concept is to place the main focus on the technological support of circularization and the corresponding innovations in business models, while the decisive role people play in this model of economy is often overlooked. Individuals with specialized knowledge, skills, and values are essential for developing and implementing circular models, making effective management decisions, and promoting rational consumption patterns. The demand for circular skills and the availability of relevant competencies can significantly differ across regions, necessitating further in-depth study. Research objective. The paper is aimed at developing a new methodological approach to the study of circular economy skills at the regional level. This approach considers these skills in terms of both employer demand and their incorporation into master’s degree programs, accounting for regional specifics. Data and methods. The study employed a comprehensive approach, integrating theoretical methods with empirical analysis. Scientometric and content analysis identified taxonomies of circular economy skills, and employers’ personnel needs were examined through the analysis of the HeadHunter job site using Python software. Additionally, the study encompassed an analysis of educational programs from official websites of universities in southern Russian regions. Results. A new approach to the study of supply and demand of circular economy skills at the regional level has been proposed and tested. As a result, it was determined that there is a demand for sustainable development specialists in various industries in the Russian labor market, which varies across different regions of the country. The relevant skills are included in the master’s degree programs offered by universities. There is a need for greater involvement of regional authorities in shaping educational demands presented to universities, as this is essential for generating demand in the job market for the corresponding competencies. Conclusions. To better achieve targets in sustainable development and facilitate the transition to a circular economy, it is essential to promote a balanced development of all the relevant skills and behavioral patterns. To ensure this, it is important to involve regional authorities in shaping the demand for these skills.

Relevance. Similar to other countries, Indonesia’s economy was significantly impacted by the COVID-19 pandemic, especially at the district and city levels. As the second-largest contributor to Indonesia’s GDP, East Java faced noticeable economic downturns. Industry, the region’s main economic sector, played a key role in these challenges, making it essential to evaluate all sectors from a regional economic perspective to navigate this turbulence effectively. Research objective. This study investigates the regional economy’s sectoral competitiveness in East Java, with a particular focus on the 17 sectors categorized by Statistic Indonesia (Badan Pusat Statistik-BPS) before and after COVID-19. Data and methods. The study relies on data from Badan Pusat Statistik (BPS)). The dataset includes GDP information for 11 regions, namely 7 districts and 4 cities, in East Java from 2018 to 2022, covering the pre- and post-pandemic periods. Methodologically, the study employed Location Quotient (LQ) analysis and Mix and Share Analysis. LQ analysis was used to assess the concentration and comparative advantage of East Java’s regions. Mix and Share and Shift-Share analyses were applied to identify the competitive industries in specific regions and their advantages. Results. The findings show positive economic growth in most regions of East Java before and after the pandemic, except for two regencies that saw a decline. The study emphasizes the need to strengthen regional resilience at the village level using the Village Fund from the national budget. Conclusions. Regional stakeholders, central government interventions, and continued development of leading sectors are essential for mitigating the effects of COVID-19. According to regional economic theory, collaboration between the government and businesses is crucial for enhancing competitive advantage and increasing the number of leading sectors.

Relevance. Uneven spatial development is a common challenge for all countries, driven by both subjective and objective factors. The issue lies not in regional disparities themselves but in their growing intensity. Amid crises and economic turbulence, it is crucial to have tools to assess the risks of increasing spatial unevenness and widening socio-economic disparities between regions. Research Objective. This study aims to develop and test a tool for estimating the risks of uneven spatial development in Russia’s macroregions and the growing differentiation of regions by socio-economic level, using the Urals-Siberian macroregion as a case study. Data and Methods. A two-stage approach is proposed to evaluate spatial development in terms of uniformity and regional differentiation by socio-economic level and growth rate. In the first stage, the probability of a socio-economic decline is estimated based on key indicators (risk factors) and their dynamic indices. In the second stage, the probability of an increasing variation coefficient within a macroregion, reflecting rising disparities in socio-economic development, is analyzed. A multifactor risk model is used for analysis. The study relies on data from the Federal State Statistics Service (Rosstat) covering the period from 2000 to 2022. Results. Applying this approach to the Urals-Siberian macroregion revealed persistent spatial unevenness throughout the study period, primarily due to the specialization of regions, which stabilizes their relative positions. However, during crises, spatial disparities tend to widen as regions demonstrate varying adaptive capacities and resilience - some not only recover but also improve their positions. Conclusion. The proposed tool assesses risks linked to uneven development and growing regional disparities, offering insights for sustainable macroregional strategies. The findings emphasize the need to consider regions’ specificities and adaptive capacities in spatial development policies.

Relevance. As interregional competition intensifies, state support for innovation in regional economies becomes increasingly important. To improve the effectiveness of such support, it is necessary to gain a better understanding of the link between innovation and economic development. Research Objective. The study aims to assess the impact of innovation activity on regional economic growth, focusing on the case of a large industrial region in Russia. Data and Methods. The analysis uses socio-economic data for Sverdlovsk region from 2000 to 2023 and applies an autoregressive distributed lag (ARDL) model to assess the relationship between innovation and economic performance. The study introduces an Innovation Activity Index, which incorporates several key components, such as the number of research personnel, internal R&D expenditures, and other relevant indicators, for a more comprehensive evaluation. Results. The study traces the region’s innovation activity, revealing a general upward trend. However, while innovation clearly has a positively influence on economic growth in the short term, its effects over medium- and long-term periods are less obvious, likely due to structural factors in the regional economy. Conclusion. The study proposes recommendations to enhance regional innovation support within the «smart specialization» framework, including backing innovation projects, developing a sustainable innovation ecosystem, and investing in human capital.

Relevance. Since regional markets are interconnected and influence each other, forecasting price changes for goods and services requires considering both time and location. Economic instability, shifting supply chains, and rising inflation expectations make this research especially relevant. Additionally, the growing need for quick responses to price fluctuations highlights the importance of adopting data-processing methods that enable near real-time analysis. Research Objective. The aim of the study was to analyze the spatial dependence of prices and the presence of brands within the context of cyclically fluctuating demand and supply across different price segments. Data and methods. This study utilized data provided by the online analytics service продажи. рф, which encompasses daily selling (registered) prices for 135 ice-cream brands across 84 Russian regions, spanning the period from January 1, 2021, to December 31, 2023. The analysis examined regional differences in ice cream prices and brand representation, as well as the spatial autocorrelation of prices, particularly in relation to seasonal demand fluctuations. Spatial autocorrelation was assessed using global and local Moran’s I indices, with spatial clusters identified based on these estimates. To explore the cyclicality of spatial autocorrelation, partial autocorrelation functions (ACF and PACF) were used, and the Kruskal-Wallis test was applied. Results. The results of the analysis confirmed the differentiation of regions in terms of ice-cream brand representation, including variations across three price segments: Elite, Standard and Economy. We found a correlation between brand representation and regional population size, but no direct relationship with regional wage levels. Further analysis of individual brand prices and their spatial autocorrelation confirmed the hypothesized presence of spatial autocorrelation and demonstrated an increase in this autocorrelation over the study period. Examination of data cyclicality indicated that time series of average prices and global Moran’s I indices exhibited significant weekly cyclicality, while annual cyclicality was not consistently detected across all analytical methods and only emerged in the analysis of average prices. This suggests that seasonal variations in production and consumption volumes do not necessarily translate into corresponding seasonal fluctuations in prices or their spatial autocorrelation for all product groups. Conclusions. Spatial price dependence is not static; its level and dynamics are significantly influenced by product characteristics, underscoring the necessity of shifting from analyses of aggregate-price indices to analyses of individual product prices. A key methodological contribution of this study is the validation of findings previously observed with more aggregated data (year/month, product group) using highly detailed daily and brand-level data. This approach enhances forecasting accuracy by capturing the full scope of regional variations in consumer behavior.