In the context of increasing economic and political risks, industry is a reliable guarantor of sovereignty of any country that ensures a decent standard of living for its population. The paper examines current global trends of industrial transformation and its regional aspects. The study aims to systematise scientific approaches to determining regional priorities, mechanisms of industrial development and criteria for optimal spatial location, as the evolution of the industrial system leads to their changes. A method of systematic literature review (SLR) was applied based on the analysis of publications relevant to the research purpose and objectives. Modern scientific literature has developed a whole range of concepts to characterise the existing industrial processes: the fourth industrial revolution, Industry 4.0, digital transformation of industry and new industrialisation. The analysis of publications has shown that these concepts are often mixed, thus, this research presented their definitions, areas of intersection and differences. Additionally, the study discusses approaches to regional industrial development and spatial location of industries, which were formulated in the scientific literature in the period 2011–2021. Three concepts revealing regional aspects of modern industrial development — regional industrial path development, «smart» specialisation and regional industrial identity — were critically analysed. The review of foreign and Russian publications can be used to substantiate niche segments of regional industrial research. The paper identified the following study areas: development of methods for choosing a new industrial path; justification of regional priorities according to “smart” specialisation; creation of effective mechanisms for implementing regional industrial and innovation policies; analysis of correlations between cluster configurations and regional innovation activity.

The negative experience of economic reforms during the 1990s showed that excessive bias towards export-import economic relations to the detriment of social reproduction, especially without reference to internal social and technological problems, threatens the integrity of the Russian market space. At present, the Arctic and other territories of the Russian North are exposed to the inherent instability of external markets for hydrocarbons and mineral raw materials. Additionally, attitudes towards energy production and consumption have undergone profound changes in recent years. In accordance with the demands of the «green economy», attention has been increasingly focused on qualitative and structural aspects in place of quantitative indicators. In order to increase production of high-quality light oil and petrochemical products that are competitive on world markets, domestic fuel and energy companies have responded by modernising oil refineries and gas processing plants. With the transition of hydrocarbon production to exploiting smaller deposits, the decline of the coal industry and a growing scarcity of in-demand raw materials (gold, diamonds, rare earth metals, nickel, copper, titanium), the economic situation in the Russian North is increasingly characterised by small forest chemistry enterprises producing commercial products for medical, agricultural and household purposes. In addition, a growth in domestic and foreign demand for organic products supports reindeer husbandry, fishing and even foraging for mushrooms and berries. An important objective for national economic decision-makers consists in the implementation of technologies critical to the development of the northern regions. In the process of strengthening the Russian socio-economic space, active interaction between participating regional governments plays a significant role. The aforementioned issues are considered in the context of spatial development theory and other concepts underpinning the formation of northern economic systems. The study findings can be used to inform Arctic strategies, programmes and long-term plans for the socio-economic development of the Russian North.

Structural analysis of regional economies plays a significant role in political decision-making. In the context of Russian regional development, a new research topic emerges at the level of economic macroregions as defined in the current Spatial Development Strategy of the Russian Federation. The present work aims to empirically evaluate the use of shift-share analysis to clarify the contribution of the neighbourhood effect in addition to national and regional growth factors. The proposed approach incorporates structural shifts of spatial interactions into the classical method using various matrices (adjacency, neighbourhood). Macroregional economic growth was decomposed on the basis of consolidated sectoral structural dynamics and national development stages from 2004–2018 to reveal specific features of structural growth. It was determined that the most significant effects at all stages are those generated by national economic policy. Regional effects are especially important for macroregions whose development is characterised by substantial state support combined with an adequate resource base. Negative values of the spatial sectoral shift persisting across all macroregions testify to the positive mutual influence of macroregional specialisation and intensified interregional cooperation. Sectoral effects were observed only for particular economic sectors or at certain macroregional development stages. Recommendations for strengthening interregional interactions are proposed on the basis of the enlarged typology of structural effects in macroregions. Comparative analysis confirmed the consistency of estimates obtained using standard and spatial shift-share methods. Future research will focus on clarifying the structure of spatial relationships and detailing actual interregional economic interactions in the form of products and goods exchanged between macroregions.

The vulnerability of regional food markets is difficult to study due to the lack of a unified approach to analysing the weaknesses of agricultural enterprises, which is necessary for investigating their response to external and internal changes. The study aims to solve this problem by developing an adaptable method for assessing the vulnerability of organisations that produce, process and sell agricultural products in regional food markets. For this purpose, we applied hierarchical mechanisms of integrated assessment for combining various indicators of agricultural enterprises into a single vulnerability score. The present research examines the alcohol market: while this particular sector is represented by a small number of producers, these organisations are usually the largest taxpayers in the agri-food industry, especially in areas of risky farming. As an example, we show how the vulnerability of Permalko JSC (a large producer of alcoholic beverages) has changed because of the COVID-19 pandemic. This company not only satisfies the needs of Perm oblast’s market, but also exports its production to many Russian regions, as well as to near and far abroad. As a result, we propose a new methodology, represented by a set of mathematical formulas, and define its variables. This versatile approach to vulnerability assessment can be adapted for any agri-food enterprise by specifying the parameters. The model is implemented in the dekon software package, which is a web application. The cloud service will provide unified access to all agricultural enterprises.

In the context of external shocks, socio-economic coherence of an industrial region reflects its ability to function successfully. Many researchers examine economic space, focusing on interaction between entities (including infrastructure) while ignoring territorial boundaries. However, it is necessary to consider a region’s endogenous core, whose historically connected elements generate evolutionary changes under the influence of external factors. This study develops tools to assess regional infrastructure coherence, taking into account the endogenous determinants of its socio-economic development. The research methodology includes: a comparison of absolute and relative territorial characteristics and infrastructure development parameters; statistical, economic and mathematical methods for determining and evaluating the resulting indicators; an expert assessment of the infrastructure potential; a matrix method for identifying the depth of infrastructure gaps. An analysis of Sverdlovsk oblast and neighbouring regions revealed infrastructure gaps of the first level of depth (insignificant, significant, stably significant), violating the integrity of the regional core, as well as gaps of the second level of depth (forming, potentially forming), requiring serious transformations of the core elements. The conducted research determined the infrastructure coherence characteristics of the regional core. Thus, the most favourable situation is in Sverdlovsk oblast, whose core has strong integrity. The most unfavourable situation is observed in Perm Krai and Khanty- Mansi Autonomous Okrug. Perm Krai’s core is characterised by minor gaps of the first level of depth and potential second level gaps. In Khanty-Mansi Autonomous Okrug, significant first level gaps are already established, while second level gaps are still forming. This situation occurred due to the industrial specificity of these regions, as well as the discrepancy between high economic activity (increasing the demand for transport services) and infrastructure development. Further research will focus on the ways to improve the regional connectivity at the intra- and inter-regional levels.

The growth rate of Russia’s total productivity has been slowing down significantly since 2008. The majority of relevant publications either describe an economic methodology or specifically focus on labour productivity. However, economic growth rates, as well as community welfare, largely depend on total factor productivity. The paper aims to determine the reasons for the slowdown in the growth of total factor productivity after 2008. This negative dynamics was assessed using a macroeconomic econometric model and estimates for Russian regions and types of economic activity. Elasticity of dependent variables was calculated based on econometric equations as well as multipliers of exogenous variables presented in the model. Ordinary and rank correlations between the variables were also examined. The calculations revealed that the stagnation of total factor productivity was caused by the misallocation of resources across industries and regions, decrease in aggregate demand, increase in capital goods prices (primarily due to rouble devaluation) and a slowdown in digital economy development. In turn, these trends were influenced by a decline in public investment and export prices, as well as a slowdown in population growth and liquidity. Simultaneously, growth of the world economy contributed to the demand for Russian export goods, preventing a decrease in productivity. The findings can be used for forecasting Russian economic trends and developing relevant policy measures. Further research will examine the role of human capital, energy intensity, climate and institutional factors in increasing the total productivity.

Regional differences in the cost of living distort the estimates of monetary components of living standards and resource requirements, which are necessary for implementing measures to reduce income inequality as a cause of social injustice and unrest. Thus, we propose a methodology for calculating nominal household income using rouble purchasing power parity to assess its influence on national inequality. This approach measures inequality based on individual data on household income, disregarding the territorial differentiation of consumer prices. Then, the influence of regional price differences on the national income inequality was assessed by comparing Gini coefficients calculated for the same sample of households using two criteria: nominal per capita income and per capita income adjusted for purchasing power in various regions. The study revealed that the difference in nominal incomes is reduced by regional disparities in the cost of living. Simultaneously, the distribution of household incomes adjusted for regional purchasing power parities is more even. The research findings can be used to develop policy measures aimed at reducing regional welfare disparities and poverty.

Universities, comprising a strategic resource in building up a region’s human capital, play a key role in ensuring sustainable economic growth. For proactive young people seeking opportunities to obtain higher education, develop professional trajectories and enhance their social connections, Russian regions lacking such facilities are seen as less attractive. This situation provokes an outflow of the most promising university candidates from the peripheral regions to the various centres of attraction. Thus, a relevant research question concerns the relationship between the quality of regional universities and the retention of young specialists, who may be expected to support the future development of industrial enterprises in the region. The assessment of interregional mobility carried out by the present study is based on an analysis of responses from applicant and graduate surveys supplemented with statistical data (Monitoring the Effectiveness of Russian Universities, Rosstat). In order to process this information, classification and data comparison methods were used. The results of the study showed that the Sverdlovsk and Tyumen oblasts are the primary centres of attraction for university entrance candidates from other Russian regions to the Urals, with the inflow of such applicants to these oblasts comprising on average 4.1 % and 13.2 %, respectively, of 18 year olds enrolling in these institutions during the 2015–2019 period. At the same time, the largest universities provide relevant training for the region’s industrial base (up to 87 % of employed Ural Federal University graduates work in the Ural Region). The research results can be used to enhance the activities of universities and employment services in terms of developing tools for attracting and retaining proactive youth, improving the mechanisms for studying postgraduate migration in order to increase the region’s attractiveness.

Employment of older people can help solve problems arising from the population ageing. The growing demand for such employees creates favourable conditions for the realisation of their resource potential. In order to identify potential sectors for the employment of older workers, the study assesses structural shifts in the labour market by type of economic activity in the Eurasian Economic Union (EAEU). It was hypothesised that, despite labour potential differences, the EAEU countries have similar industries characterised by positive trends toward increasing employment of older workers. After identifying these trends, the research classified theoretical approaches to the study of employment opportunities for older adults. The assessment of structural differences in employment by type of economic activity was conducted based on the selected methodology. To quantify changes in the EAEU countries, employment of older workers was analysed using the integral coefficients of structural shifts of Gatev and Ryabtsev. According to statistics on the population employment for 2014–2019, older people of the EAEU countries (except Armenia) can continue to work in real estate transactions, hotels and public catering establishments, as well as in the field of health care and social services. To stimulate the employment of older workers in these areas, state measures, based on the proposed recommendations, can focus on promoting entrepreneurship and expanding the information environment for older people.

The present study attempts to answer the question, which is not considered in the United Nations’ annual Human Development Reports, namely, how spatial patterns of the world countries differ in terms of human development indices. The quantitative research includes three phases. First, functional relations between indices were analysed based on Moran’s I and data fitted by linear regression. Second, clustering of the world countries by human development indices revealed seven spatial clusters. Third, the countries were classified by the types of significant human development problems. The classification distinguished various types of countries: prosperous, problematic and problematic in certain areas. Correlation and spatial dependence analysis demonstrated an important relationship between education and child indicators, in particular, years of education and life expectancy. As a result, the territorial concentration of countries with similar human development was noticed. According to all four groups of indices, 51 prosperous countries (the majority of which are members of the Organisation for Economic Co-operation and Development (OECD)) are characterised by the lack of serious problems. The group of problematic countries includes 51 territories mostly located in sub-Saharan Africa, as well as in Asia, Latin America and Oceania. The findings on relative similarity observed in the identified clusters and groups can be used for developing standard solutions to improve human development. Further research in this direction seems promising.

Knowledge and skills concentrated in human capital are increasingly important factors of economic development. However, there is a lack of a methodology for determining, which skills are necessary for the efficient industrial development. To this end, we examine skill requirements of regional employers potentially leading to an increase in economic indicators. Skills in demand were compared with predicted indicators based on a semantic content analysis of vacancy databases in various regions of the Russian Federation. It was revealed that the list of demanded competencies depends not on a geographical aspect but on a specific profession. An analysis of the obtained data demonstrated that the growth in demand for highly qualified employees in the Russian Federation is correlated with an increase in gross value added of relevant industries. A linear correlation between gross value added per employee and the need for skilled specialists was demonstrated on the example of the transport sector. The proposed methodology can be used by educational organisations for targeted training of specialists, as well as by employers and experts for forecasting medium- and long-term socio-economic development of Russian regions.

A quantitative assessment of human capital is necessary for both understanding society and implementing effective socio-economic policies. In the present paper, a new approach — the Human Life Indicator (HLI) — was implemented to measure inequality in life expectancy. The Human Development Index (HDI), proposed by the United Nations, does not take into account significant internal inequalities of countries with the same or similar life expectancy. On the contrary, HLI reflects the well-being in terms of years of life, additionally considering the inequality in life expectancy. Presented calculations were based on federal mortality statistics. This study estimated human development of Russian federal districts by comparing HDI and HLI. The analysis revealed that high HDI values, achieved, for example, due to a high gross regional product (GRP) per capita, do not translate into an improvement in the quality of life for the majority of the population. Such situation is observed in the Far Eastern Federal District. The regions that are relatively prosperous in terms of HLI are concentrated in the European part of Russia and the North Caucasus Federal District. Simultaneously, most Siberian and the Far Eastern regions, characterised by high inequality in life expectancy, require the attention of federal and regional authorities. The presented approach to assessing the success of regional development can be used to estimate how the ongoing socio-economic policy and health care reforms influence the quality of life in the regions. This method can also be applied to compare inter-regional indicators of human capital and monitor changes in well-being of the population.

The present paper analyses migration policy measures implemented in the Russian Far East, namely, State Programme to Assist the Voluntary Resettlement of Compatriots Living Abroad to the Russian Federation, the Far-Eastern Hectare Programme, establishment of Priority Development Areas (PDAs) and territories with a special regime of economic activity. The synthetic control method was applied to quantitatively assess how the adopted measures affect the migration outflow from regions of the Far Eastern Federal District. According to this method and relevant statistics, constituent entities of the Far Eastern Federal District were compared with control regions of the Siberian Federal District, where these policy tools have not been introduced. Comparable areas had similar socio-economic development trends and migration flows in the period preceding the implementation of the state programmes. To analyse the impact of migration policy changes in 2011–2018, the difference between outflow values of the Far Eastern and synthetic control regions was calculated. The results showed that the average estimated values are negative and significantly different from zero. This indicates a positive effect of new migration mitigation measures on reducing the outflow from the Russian Far East. Future research will separately assess the effectiveness of each migration policy tool implemented in the Far Eastern Federal District.

While scientific studies have not reached a consensus on the methodology for examining Technical Efficiency (or Inefficiency), the influence of regions appears to be important for efficiency scores. Therefore, this research aims to investigate the empirical procedures for the achievement of more robust results in the analysis of productive efficiency, as well as to evaluate the effect of the location of farms on such efficiency. The goal was to check whether the most developed regions are the most efficient. Meta-regression analysis provides an adequate method for an accurate assessment of both situations. This technique was applied based on a database of 166 observations on the agricultural sector from countries around the world, published in the period 2010–2017. The criteria used for the database collection and for the conceived model were not previously used and, thereby, enrich the discussion on the topic. The procedure aims to check the variation in the Mean of Technical Inefficiency and conduct an analysis using Quasi-Maximum Likelihood Estimation. The regressions showed that the Mean of Technical Inefficiency could be mainly explained by data, variables, employed empirical models and the region of study. The studies that focus on farms of developed countries present the lowest Mean of Technical Inefficiency, while studies for developing or low-income countries exhibit the opposite. Therefore, for future research on productive analysis, we suggest empirical procedures aimed at achieving robust results that take into account specific regional characteristics of farms.

The quality of online learning mechanisms, widely implemented due to the COVID-19 pandemic, is a significant issue for regional higher education systems. The research aims to assess student satisfaction with the quality of online education by identifying discrepancies between their requirements and the actual learning process. In order to examine the gaps between students’ expectations and perceptions, a new approach was proposed based on the integrated use of Gap analysis and SERVQUAL methodology, combining qualitative and quantitative aspects. SERVQUAL questionnaires for measuring student satisfaction with online learning include the following criteria: tangibles, reliability, responsiveness, assurance, empathy. Full- and part-time undergraduates of humanitarian and socio-economic departments of two universities participated in the study. Ural Federal University bachelors, learning via Moodle and Microsoft Teams platforms, could directly communicate with their peers and professors, while students of National Research Nuclear University MEPhI were engaged in massive open online courses (MOOC). As a result, all five criteria were analysed in the proposed model for quality assessment of online learning to reveal the gaps between students’ expectations and perceptions of the educational process. Significant discrepancies in the «empathy» and «responsiveness» criteria in both groups demonstrate low student satisfaction with the quality of communication and individualisation of learning. The research findings can be used to construct resource allocation models for implementing educational programmes and developing support measures for regional higher education institutions.

As factors affecting interregional interactions play an important role in regional economic development. Thus, developing a methodology for assessing these interactions is becoming urgent. The article proposes a methodological approach to analyse the factors influencing possible interactions between Sverdlovsk oblast and other constituent entities of the Russian Federation in the manufacturing industry. It is hypothesised that the elements of an interregional interaction matrix are proxy variables characterising the degree of this interaction. An economic analysis of relations and production chains between Sverdlovsk oblast and other constituent entitles confirmed this hypothesis. First, based on the spatial distribution of manufacturing output in the examined regions, values of an indicator showing the strength of their mutual influence were determined. Second, the impact of economic, infrastructural and institutional factors on the obtained indicator, characterising the interaction between Sverdlovsk oblast and other regions, was assessed using quantile regression. In this case, such a technique was chosen instead of the classical ordinary least squares (OLS) regression that incorrectly estimates the dependencies between the studied variables. This is expressed in the fact that the regression coefficients depend on q-quantile of the dependent variable. We have revealed that price levels of the examined regions do not affect their possible interactions with Sverdlovsk oblast. Simultaneously, the dissemination of knowledge acts a driver of interaction between the considered regional manufacturing industries. The research findings can be used to prepare strategies, programmes and schemes for the placement and development of industries, considering the potential of Sverdlovsk oblast and other Russian regions.

There has been a lot of debate in global politics about fair trade, surpluses (also called positive trade accounts), and deficits (negative trade accounts) among the USA, China and the European Union (EU). The study aims to analyse the countries’ trade accounts through the lenses of international finance theory. Based on financial analytical models, the countries’ competitiveness and changes in their net foreign wealth were examined. The factors considered in the literature review are as follows: exchange rate, government tariff and tax policies, saving rate, manufacturing base, investments, natural resource abundance and others. The computation of the trade accounts was conducted using the ten-year international trade data (2009–2018) for the EU-28 member countries that became the main importer for China instead of the USA in 2019. The conducted empirical research showed that Chinese trade has continuous deficits throughout European countries, and in some countries, it could be considered as an increasingly important structural issue (for example, in Poland and the Czech Republic). Trade with the USA, in turn, typically produces surplus for European countries, where Germany is the leader. The provided conclusions hold value for international trade managers in terms of their potential influence on public policy in the researched countries. In light of the financial crisis, the current export shock could be used by countries as an occasion to change the course and depart from the assumptions, which do not advocate for free trade.

Whether applying to individual countries or unions, the comparability of statistical indicators and their compliance with contemporary international initiatives is a serious problem. In particular, analysis of the macroeconomic indicators used for assessing the sustainability of the Eurasian Economic Union (EAEU) countries has shown that they do not reflect the actual situation. In this regard, the creation of a unified system of indicators for determining the socio-economic sustainability of EAEU member states — as well as the EAEU as a whole — becomes an urgent task. Therefore, the present study aims to refine the system for measuring the socio-economic sustainability of the Eurasian space and develop recommendations for the selection of key parameters. By comparing socio-economic sustainability indicators published by international organisations (UNECE, OECD, Eurostat, CIS Statistical Committee) in the context of the development strategies of individual EAEU countries and the Union as a whole, the authors distinguish between basic and extended indicator types. Basic indicators comprise: the annual consolidated budget deficit; general government debt; annualised inflation rate; contribution of high-tech and knowledge-intensive industries to gross domestic product (GDP); contribution of innovative goods and services to total industrial exports; growth index of the proportion of reconstruction and modernisation investment to total capital investment; fertility rate; life expectancy at birth; poverty rate. Extended indicators include: GDP; economic growth; main international trade; external and national balance of payments; social. The applicability and relevance of the proposed system for measuring the socio-economic sustainability of the Eurasian space is confirmed by statistical analysis of EAEU member state data (including correlation analysis). The results showed that the presented system of indicators reflects the actual development of the EAEU countries, contributing to informed decision-making both at the level of the EAEU member states and at the level of the Union as a whole.

The literature emphasises the role of regional and local innovation environment. Regional Innovation Systems show differences in innovation outputs determined by different inputs. Understanding these relationships can have important implications for regional and innovation policy. The research aims to classify Regional Innovation Systems in Poland according to their innovation capacity and performance. The analysis covers 72 subregions (classified as NUTS 3 in the Nomenclature of Territorial Units for Statistics) in 2004–2016. Classes of Regional Innovation Systems in Poland were identified based on a combination of linear and functional approaches and data from published and unpublished sources. It was assumed that innovation systems in Poland differ due to their location in metropolitan and non-metropolitan regions, thus, the Eurostat NUTS 3 metro/non-metro typology was applied for this purpose. Panel data regressions as models with individual random effects were estimated separately for metropolitan and non-metropolitan groups of subregions. The study identified common determinants of innovation outputs in both NUTS 3 types: share of innovative industrial enterprises, industry share, unemployment rate, and employment in research and development. Next, NUTS 3 were classified within each of two analysed types in line with output- and input-indices, the latter being calculated as non-weighted average of significant inputs. Last, the subregions were clustered based on individual inputs to enable a more detailed assessment of their innovation potential. The cluster analysis using k-means method with maximum cluster distance was applied. The results showed that the composition of the classes identified within metropolitan and non-metropolitan systems in 2004–2016 remains unstable, similarly to the composition of clusters identified by inputs. The latter confirms the changes in components of the capacity within both Regional Innovation System types. The observed situation allows us to assume that Regional Innovation Systems in Poland are evolving. In further research, the efficiency of Regional Innovation Systems should be assessed, taking into account the differences between metropolitan and non-metropolitan regions as well as other environmental factors that may determine the efficiency of innovative processes.

Nowadays, more than 700 smart city projects are developing worldwide. Smart-green integration in urban regions stimulates the development and implementation of the smart sustainable city (SSC) concept. The present research aims to analyse and classify modern approaches to this concept, as well as to identify which one is the most promising. Both rejecting and affirmative approaches to the topic of SSC were taken into account. We conceptually investigated and systematised modern affirmative approaches — technocentric, socio-economic, green economic and human-oriented ones. The analysed data on the smart sustainable city concept includes scientific works published and indexed in the international citation databases (Scopus and Web of Science), reports of the Organization for Economic Co-operation and Development, the United Nations General Assembly, the International Energy Agency, as well as the authors’ survey results from previous research. The paper highlights the current trend of the dominance of sustainable and human-oriented approaches in the smart sustainable city concepts and the growing importance of smart urban communities. The examination of the EU case study demonstrated the important role of sustainable development and wastewater treatment in evaluating and ranking smart sustainable. The obtained results demonstrate that 75 % of SSCs from the Lisbon ranking stated waste treatment as their priority. Only 7 of 28 (25 %) chosen cities did not achieve great results in this area. This fact proves the priority of waste treatment in the development of the smart sustainable city concept. The findings confirm that the research results could be implemented in smart sustainable cities around the world.

The current crisis, as well as complicated economic relations between countries, sustainable development risks of global value chains (GVCs), and international trade protectionism cause changes in the modern system of global foreign direct investment (FDI). Due to the complexity of these risks and the vulnerability of the world economy to future global recessions, it is necessary to develop a new concept of cross-border capital flows in the form of FDI. The research aims to identify structural changes in global FDI in the context of international trade and capital market challenges. Structural and dynamic analysis and a descriptive assessment were conducted to examine global foreign direct investment in the system of international capital movement, taking into account the unstable economic environment. A test of the impact of the current coronavirus crisis revealed that the retrospective transformation of global FDI occurred due to changes in the internationalisation of companies, cross-border mergers and acquisitions, and regional structure of FDI. Corporate disinvestment and the growing importance of intangible assets also played an important role. As a result, the slowdown in global FDI led to a decline in reinvested earnings in many economic sectors. As the long-term recovery of the world economy will be largely determined by the dynamics of global FDI, transnational companies (TNCs) should consider local crises and strive to geographically distribute capital investment. The research revealed that the differentiation of national GVC strategies and new approaches to foreign outsourcing of TNCs are the main risks of regionalisation or nationalisation of global value chains and a corresponding decrease in FDI. The findings can be used to modify well-known FDI concepts, taking into account their impact on modern international economic relations.

Studies on the impact of government expenditures on regional and municipal development mainly focus on examining local budgets. Simultaneously, each territory has various channels for financing public needs and collecting taxes and other payments. Therefore, this research develops and tests a methodology to construct the public sector financial balance at the municipal level. The presented approach in based on the System of National Accounts (SNA), which considers expenditures and revenues of the federal, regional or municipal budgets as a single institutional sector, regardless of their affiliation. Therefore, in order to achieve the municipal financial balance, it is necessary to analyse tax payments at various budget levels, grouping them in accordance with the SNA classification. For calculating municipal expenditures, an original technique was developed to consider the costs of all public sector financial flows, including direct federal and regional sources. We use official information on municipal payroll obtained from the Federal State Statistics Service database. The net lending/borrowing ratio is taken as a balance indicator of supply and use. Public sector financial balances were constructed for 69 municipalities of Sverdlovsk oblast. Calculations have shown that, on average, public sector expenditure is almost equally divided between regional and federal budgets (one half) and municipal budgets (another half). Various municipality types were identified: 9 donors of public administration resources in Sverdlovsk oblast; 5 territories (including Ekaterinburg city) with a moderate deficit of internal resources; 35 municipalities with a significant lack of finances; 11 areas completely dependent on public administration resources. This work is part of the research aiming to develop the System of Territorial Accounts, tat is, an SNA analogue that can be implemented at the regional and municipal levels.

The issue of increasing budgetary independence and security is relevant for the majority of territorial systems, both at the regional and municipal levels. It was hypothesised that changes in the structure of regional public debt have a negative impact on their budgetary security. According to this hypothesis, an increase in the proportion of bank borrowing and corresponding decrease in the issue of debt securities by the constituent entities of the Russian Federation leads to a greater overall debt burden on the regional budget. In order to study transformation processes affecting budgetary independence and regional security. We developed a methodology to permit a separate assessment of these concepts. According to this approach, we propose to evaluate the budgetary independence of regional systems in terms of: (1) the balance of the budget (ratio of internal tax and non-tax revenues to budget expenditures); (2) financial dependence on transfers and subsidies from budgets at other levels; (3) budget security, taking into account gratuitous and non-gratuitous transfers. Thus, budgetary security can be assessed in accordance with the public debt dynamics, as well as the level of budgetary debt covered by the region’s own tax and non-tax revenues. The novelty of the presented methodological approach consists in its systematic use of Moran’s I for various spatial weight matrices combined with regression analysis methods based on panel data. Testing this methodology demonstrated the spatial heterogeneity of regional fiscal capacity, highlighting the financial dependence of most regions on federal and other gratuitous transfers. Autocorrelation analysis carried out according to Moran’s I using various spatial weight matrices confirmed the increasing tendency of the budgetary debt of Russian regions towards spatial heterogeneity. Future studies will focus on simulating the influence of various factors on regional budgetary security in order to predict the dynamics of its change.