The desire to assess the value of natural resources led to the emergence of the evaluation theory in environmental economics. However, the lack of a systematic approach to the natural resources evaluation, as well as undefined assessment boundaries hinder the development of the such a theory, including the concepts of ecosystem services and total economic value. Based on the review of relevant scientific publications, the paper aims to analyse the evolution of the evaluation theory in environmental economics, as well as to reveal its general trends and phenomena. The methods of systematisation and content analysis were applied along with evolutionary and regional approaches. The example of the natural resources development in the northern regions was used to trace the evolution of the evaluation theory in Russia. A number of basic trends and phenomena in the development of the examined theory were identified. An axiological (subjective) value has been converging with an objective value of natural resources due to the integration of various assessment factors: 1) utilitarian (early 19th — mid-20th centuries); 2) utilitarian and social, utilitarian and ecological (mid-20th century — the turn of the 20th-21st centuries); 3) utilitarian, social and ecological in aggregate (early 21st century — present day). The evaluation object (territorial aspect) has also been expanded from local assessment to the assessment of the natural resource potential of regions and the world. The paper demonstrates that the evaluation theory in environmental economics, which now considers utilitarian, social and ecological aspects, will continue to develop by creating new paradigms, approaches, methods and techniques for assessing the value of nature resources in order to converge the axiological and objective values.

Considering the widespread of Covid-19 and its impact on the population health in Russian regions, it is necessary to examine the impact of the pandemic (as excess mortality) on the regional socio-economic development in 2020. Based on a quantitative and qualitative model, the study explains the process of coronavirus diffusion at the regional level, using information from foreign publications, Russian regional statistics and a database of legal documents «Consultant +». The concept of spatial diffusion, developed in the 1950s-1980s, was chosen as the research methodology. The study methods include a cartographic analysis of the monthly dynamics of coronavirus spread in Russian regions and regression analysis of regional differences in excess mortality regarding the most significant explanatory variables. The developed regression model explains the spread of Covid-19 across Russian regions in 2020, while the proposed qualitative model «network-place-scaling» describes the spatial diffusion of the virus. The conducted analysis confirmed the relationship between the spread of the virus and economic specialisation of regions. Simultaneously, such widely discussed factors as physical density, urbanisation level and per capita income did not show significant correlation with excess mortality. The study revealed the following results. There is a significant discrepancy between the actual situation in Russian regions and expected developments according to the simplified centre-periphery model. The important regression variables, explaining the interregional differences in excess mortality in 2020, include the share of employed in contact-intensive wholesale and retail trade and manufacturing (large production teams); proportion of the population over 65; the number of retail facilities per 1000 people. The qualitative model «network-place-scaling» was deemed suitable for explaining the mechanisms of the spread of coronavirus in Russian regions. Future studies should focus on examining the mechanisms and socio-economic consequences of the pandemic at the municipal level of large cities and urban agglomerations in Russia.

Recent inclusion of the issue of economy decarbonization in the global agenda has been affecting social and political priorities. To lower greenhouse gas emissions, Russian economy has to reduce anthropogenic emissions and maximise the carbon sequestration potential of national forests. The paper demonstrates that Russian forest ecosystems compensate for more than a quarter (almost 27 %) of anthropogenic emissions. However, due to the absence of a reliable, time-tested forest inventory system in Russia, as opposed to leading countries, it is difficult to ensure the sustainable use of forest resources and full accounting of greenhouse gas absorption by forests. The research analyses systemic measures to improve the absorptive capacity of Russian forests as a key element of the mechanism for compensating industrial greenhouse gas emissions, since the global expert community should recognise the contribution of these forests to the global climate change mitigation. Potential economic benefits of increasing the carbon-absorbing capacity of forests are assessed at the regional level. The example of Irkutsk oblast shows that the calculated effect of the analysed measures can amount to 6–7 dollars/ha at the current price of carbon credits; full implementation of these measures in the region can bring up to 480 million US dollars annually, net of expenses. The research proposes to ensure the necessary quality and completeness of data of the State Forest Registry by integrating remote and ground-based field measurements. It is also suggested to enhance institutional and investment support to state forest conservation initiatives, including in the framework of the National Project “Ecology” and forest-climate projects based on public-private partnerships. These measures should be included in the reform of public policy in the field of forest management.

Sustainable development was chosen by the United Nations as the key concept of the future in the 21st century, which led to the emergence of other economic concepts, such as green and blue economy, seen as contributing to the achievement of sustainable development goals (SDGs). In Russia, despite the ongoing processes of green transformation in some economic sectors and certain improvements in the green legislation and green finance, not all businesses and regions are ready to embrace sustainable development. This paper discusses two interconnected aspects of regional economic systems — their economic efficiency and environmental impact. The analysis focuses on the regions of the Ural Federal District and explores these regions’ transition to sustainable development by looking at their eco-intensity. Methodologically, the study relies on the methods of analysis and synthesis, statistical, comparative and causal analysis. Conceptually, we use the theoretical framework of sustainable development as a point of departure for our discussion. The results have shown, on the one hand, a decrease in the industrial pressure on the natural environment, related primarily to the enhanced resource efficiency of certain industries. On the other hand, less effort is now invested into minimising the negative impact on the environment in Ural regions. We have also identified those areas of sustainable development that hold most promise in the Russian context. Our findings can serve as a basis for the strategies of regional sustainable development and may be used for further research on socio-environmental and economic sustainability.

Global climate change threatens the continued existence of mankind. The rate of warming in Russia, which is 2.5 times higher than the rate of growth of the global average temperature, can lead to huge environmental and financial losses. Thus, it is increasingly necessary to modernise and develop methods and tools for adaptive regulation of national climate policy to increase its efficiency at the regional and federal levels. To this end, the methods of content analysis, grouping, modelling, comparative and correlation analysis, as well as an information asymmetry approach were used in the research. The paper substantiates the necessity of a transition from autarky and directionality to the integration of regions and the federation based on adaptation and preventive measures. The periodic assessment of climate change and relevant contributing factors should be replaced by the continuous management and regional monitoring of climate risks. Stressing the importance of transparency and comparability of information on climate risks, the research distinguished anthropogenic risks, risks of reducing the quality of life and moral climate risks. In order to promote climate preservation, an organisational and economic mechanism for the implementation of climate policy was developed, whose main function is the regional environmental management. Assessment of the decoupling effect and ranking of the constituent entities of the Russian Federation in terms of the relationship between energy intensity and climate intensity proved the feasibility of using the proposed indicators to increase the efficiency of the organisational and economic mechanism. Regulatory and financial support for the mechanism can be provided by introducing a quota market, green certificates and bonds, insurance and risk hedging strategies based on a scenario approach and online-management models. The research results can be used for the digitalisation of national climate policy, as well as for the development of regional and municipal climate strategies, programmes, projects.

2018 FIFA World Cup became the first championship held in Russia and Eastern Europe. However, at that time, Russia already had experience in hosting sports mega-events such as the 2014 Winter Olympics in Sochi, the 2013 Summer Universiade in Kazan, and before that the 1980 Olympic Games in Moscow. Hosting the championship in 11 cities at once sets the 2018 FIFA World Cup apart from all these events. It gave impetus to the socio-economic development of all cities (and regions) where the matches were held, including Ekaterinburg. On the other hand, the sports mega-event provides unique opportunities for the global marketing positioning of the city. The present study examines the challenges of developing a city marketing strategy using the case of Ekaterinburg. Theoretical foundations of place marketing were employed for the analysis. Based on the critically explored concepts of place marketing and the competitiveness of the territory, the author’s 4C + 1S model was constructed. The current state of the urban environment was evaluated using a SWOT analysis conducted in a group of students. The research also analysed cities’ experience in conducting recent sports mega-events in the world and managing their facilities and infrastructure after these events. In conclusion, we formulated the proposals for Ekaterinburg’s positioning, including the improvement of the transport system, solution to environmental problems, increase in the effectiveness of the local government, and maintenance of public consensus. As a basis for specialisation, it is suggested to consider either the industry of meetings (MICE) or industrial tourism with complementary ‘natural’ and ‘historical’ directions. The proposed 4C + 1S model can be used as a methodological framework for the creation of urban marketing strategies. Additionally, the article makes a theoretical contribution to the development of place marketing. The results can be applied in further academic urban studies.

The Strategy of Spatial Development of the Russian Federation until 2025 aims at the economic growth acceleration and reduction of the intra-regional socio-economic differences. Therefore, the factors affecting the economic growth of regions, convergence of regions, spillover effects from the neighbouring regions are of importance. Russian regions are very different and do not converge to a unique equilibrium path. 80 Russian regions were divided into the groups of poor, middle and rich regions. Three main hypotheses were considered, based on the differences in the 1) convergence speed, 2) influence of the same factors, 3) different mutual influence of regions. They were tested using a modified spatially autoregressive model for the three groups using the Russian regional data for 2000–2017. Beta-convergence was found only for the middle and rich regions, the rate of convergence was higher in the rich regions. The poor regions did not grow faster than the other regions, confirming the relevance of the Strategy of Spatial Development. The similarities and differences were identified in the factors ensuring the economic growth of regions belonging to the three groups. The growth in all regions is stimulated by the regional economy openness. The growth of rich regions can be achieved by increasing the investment and reducing the investment risk. However, the investments in the poor and middle regions are not effective. The poor and middle regions receive positive spillovers from the growth of the neighbouring regions. It is possible to expect reduced differences in the living standards between the poor and rich regions.

When investigating healthcare efficiency at the regional level, the problem of interactions between neighbouring locations arises. The health of the population in a given region is related to the healthcare in other areas through a medical tourism, a limited number of highly specialised institutions, competition between institutions, etc. Ignoring these inter-regional links may result in a systematic bias in the efficiency analysis. Similar issues may hinder any regional studies. Hence, the main purpose of this paper is to introduce a new approach to measuring efficiency in regional studies through spatial data envelopment analysis (SDEA). The paper offers a proper mathematical formulation of the new methodology and highlights differences between classic data envelopment analysis (DEA) and the newly developed method. The motivation for seeking a new solution to the problem of spatially adequate assessment of regional efficiency is derived from the literature review and a discussion of the presented theoretical examples. The classic DEA allows for multidimensional analysis of the performance of homogenous independent decision-making units. However, in regional studies, an area where DEA has gained popularity, the assumption of the isolation of decision-making units seems to be unfounded. In the SDEA approach, the region-specific spatial context is incorporated into the analysis via the W matrix and spatial interactions are reflected in the model through spatially weighted inputs and outputs. Therefore, in our paper, we verify the hypothesis that spatial interactions are an indispensable factor of regional efficiency analysis. A study of healthcare efficiency in European regions is presented as an illustration of the utility of the new methodology. Furthermore, we compare the results of the classic DEA approach with those of the SDEA, which is augmented with the spatial equivalents of inputs and outputs. Our results suggest that classic DEA undervalues regional healthcare efficiency by underestimating the region-specific spatial context.2 Researchers may find the introduced SDEA method useful in all space related fields when investigated phenomenon exhibits spatial autocorrelation. In particular, the new approach may deepen the regional efficiency analysis of innovation, development, logistics, tourism, etc.

Russian regions are known to be economically different. While economic inequality is quite natural for a large country, it can lead to depopulation of less developed regions. Thus, the scale of this phenomenon should be assessed and taken into account in development programmes of the Eastern regions of Russia. The study aims to examine population dynamics and migration processes occurring in Asian Russia in the first decades of the 21st century, focusing on the role of human capital at different stages of regional economic development. Migration losses and gains of Asian Russia were estimated based on information on internal migration of the population by education level and the author’s approach to assessing the accumulated human capital. The calculations confirm a hypothesis that losses from the population outflow in the studied region exceed its gains from the inflow, negatively influencing the possibilities of accelerated economic growth. The conducted research presents new results concerning the outflow of human capital from Asian Russia in the period after 2008. Considering foreign experience in reducing negative effects that have also been recently observed in the region, it is proposed to intensify efforts in three major areas: new knowledge as a factor of spatial connectivity; consolidation of the population; implementation and support of economic activity in Asian Russia. The calculation results can be used in development programmes of the Eastern regions of Russia.

The population migration has attracted attention for more than a decade. As migration consequences differ in terms of characteristics and directions, governments worldwide are looking for solutions to regulate migration flows. The study aims to systematise push-pull factors of migration by analysing existing cases, as well as to build a model for predicting migration considering the quantitative interpretation of such factors. While migration factors are quite similar regardless of the country of residence, their main differences are compatibility and hierarchy. The most frequently mentioned factors include the expectation of income increase, improvement in the quality of life, professional aspects. Simultaneously, a certain pattern emerges: if a migrant’s material and economic needs are satisfied in the country of departure, they pay more attention to intangible/non-economic benefits (quality of life, infrastructure, etc.). A dynamic forecasting model for scientific migration has been developed based on the theory of positional games. The model demonstrates the changes in migration flows by describing the behaviour of a rational individual who seeks to maximise benefits from migration. The result of the simulation is a short-term forecast of trends in scientific migration of Ural scholars to key migration countries. The model predicts the intensification of migration flows to the leading Asian countries, their alignment with flows to America, and a decrease in migration to European countries. This forecast is characterised by a direct dependence of the dynamics of scientific migration flows on the socio-economic development of migration destinations. Practical implications of this study include the development of a predictive model describing migration flows in the short term as an analytical tool and systematisation of pull-push factors as key indicators for managing the migration flows of scientists. In addition, the research proposes measures positively affecting the balance of scientific migration.

Satisfaction with working time gains increasing importance in the context of changing sphere of work, spread-out of flexible forms of employment, digitalisation and telework in the recent times of the Covid-19 pandemic. The paper focuses on the factors associated with satisfaction with working time in European countries before the pandemic based on data from the European Quality of Life Survey (2016). The study serves as a basis for further comparison of the trend in working time satisfaction in the pre-pandemic period across Europe and the recent period of increasing flexibilisation of work, digitalisation and spread-out of distant employment. For this purpose, descriptive statistical analyses and two-level random intercept model for binary responses are applied. The results show that women report higher satisfaction with working time compared to men. Satisfaction significantly increases after the age of 40. The number of children and the presence of children below the age of 6 in the household are negatively associated with satisfaction with working time. Satisfaction is positively associated with income and education. Structural conditions, such as economic development measured by gross domestic product (GDP), influence Europeans’ working time satisfaction. In the Balkan countries, satisfaction with working time is the lowest, while in the North-Western societies the highest percentage of workers are satisfied with working time before the Covid-19 pandemic.

Since 2008, Russia has been conducting special surveys on the occupational structure of employed in the form of a federal statistical observation «On the number and needs of organisations for employees by professional groups». The present study aims to assess the data obtained from this observation for 2008–2018, as well as to compare the methodologies of Federal State Statistics Service (Rosstat) and the International Standard Classification of Occupations (ISCO-08). The impact of such relevant skills as emotional intelligence and data literacy on vocational training and the emergence of new professions associated with information economy is discussed. The comparative analysis demonstrated that the economy demands highly-qualified specialists in all Russian regions. Simultaneously, the research revealed the impossibility of considering the specificity of regional structures due to the insufficiency of information for predictive assessments of structural changes and the lack of data on occupations in small business and financial and social insurance sectors. According to the analysis of the dynamics of vacancies for various groups of occupations, the linear trend in the total amount of vacancies tends to decrease. The absence of relevant regional data prevents an in-depth analysis of regional differences and the construction of econometric models to identify the reasons for these differences. Additionally, it is impossible to assess the determinants of the lack of qualified staff by professional groups in Russian regions without these data. The study concludes that researchers and experts, using the Rosstat methodology, should not synonymise the concepts of occupation, speciality and type of activity. The research results can be used to expand Rosstat’s survey of occupations, in particular, its database for Russian regions, as well as to improve the methodology for statistical observation of occupational structure of the employed.

In the context of digital transformation of the economy, human capital development depends on differences in earnings. Previous studies examined the relationship between wage differentiation and employee competencies without considering the regional digitalisation. The present research tests a hypothesis of the dependence of wage differentiation on individual digital competencies, likelihood of job computerisation and digital development of a region. Linear regression method based on Mincer equations was utilised. The empirical basis comprises data from the Russia Longitudinal Monitoring Survey — Higher School of Economics (RLMS-HSE) and statistics of the Federal State Statistics Service on the digitalisation of Russian regions in the period from 2003 to 2018. Development opportunities and threats have been conceptually identified in terms of substitution and supplementation of labour, distribution of entrepreneurial risks, the use of digital competencies and the influence of regional digitalisation on differences in individual earnings. The revealed professional polarisation of the Russian labour market due to digitalisation creates unequal opportunities for income growth and professional development in the mid-term. In contrast to previous studies, this research analysed how the likelihood of computerisation affects wages, showing that while, in general, digitalisation creates an advantage for human capital, an increase in computerisation reduces earnings by almost a quarter. High level of digitalisation of certain regions supports human capital, yielding a wage increase of 5–10 % on average. The study results can be practically applied to support strategic decisions for the development of digitalisation at the local and regional levels. Moreover, the necessity to monitor professions under the threat of digital automation in regions is shown.

The Russian manufacturing sector is concentrated in regions considered as potential centres of technological development, productivity growth and long-term export opportunities. Realization of this potential requires the timely implementation of effective support measures. Using relevant statistics, the study aims to analyse how budget subsidies affect the dynamic and structural aspects of the development of Russian industrial regions. The research methodology is based on assessing the total budgetary cost of government support and correlating it with regional industrial indicators. To this end, data from the Treasury of Russia, statistical indicators, industry databases and target indicators were examined. The study revealed that government subsidies not always positively affect the industry target parameters, even distorting market mechanisms. In general, the implementation of state programmes in Russia has led to an increase in export volumes, costs for innovative activities and labour productivity with stable employment in industry. However, in industrial regions, an increase in the share of the manufacturing sector does not cause an increase in economic growth. In addition, fixed capital investment in the manufacturing sector is lower in these regions. A sharp increase in the number of high performance employees due to the implementation of support measures was observed in Russia and individual industrial regions. In terms of innovative activity, the number of patent applications in industrial regions is significantly lower than the national average. The efficiency of industry support measures in the Russian Federation can be re-evaluated based on the obtained results. Future research will focus on further detailing the budgetary cost of government support and assessing its long-term results.

Nowadays, regional container transport systems operate in the context of incomplete information and lack of integration of economic entities. Pursuance of personal economic gains by companies often leads to an imbalance in the development of regional terminal capacities, irrational empty container flows and a decreased efficiency of the regional container system in general. The present article proposes an approach to the integrated management of the regional container transport system based on the coordinated container flow distribution between terminals. This technology aims to increase the efficiency of the whole system, including due to the flow enlargement and the accelerated container trains formation. The approach involves the data sharing between cargo owners, terminals, the railway and resource owners on a digital logistics platform that forms logistics chains taking into account the transportation geography, infrastructure capacity and the interests of container market entities. The research presents a mathematical formalisation of the optimal container delivery chains by the time criterion, as well as a model of the integrated distribution of container flows between terminals. The model distributes the total container flow generated by a region between the existing terminal facilities in a way to minimise the total time of cargo delivery (taking into account the accumulation time of the full-length container block train at the terminal). The model, tested in the conditions of the container transport system in the Ural region, showed that an integrated management approach reduces the average container delivery time by 5 days due to the flow enlargement and regular container block trains. The effect size depends on the total regional container flow, as the larger number of requests for transportation to a certain destination leads to the accelerated formation of loaded container trains. The proposed technology is of economic interest for various participants of the container transport system. For cargo owners, it reduces the delivery time and, consequently, increases the capital turnover; for container owners, it accelerates the container turnover and reduces empty running; for terminals, it increases the throughput by reducing the accumulation time. To improve the model, it is planned to develop approaches for coordinating not only outgoing, but also incoming container flows between existing terminals.

There are numerous studies on different aspects of the impact of hydrocarbon production on Russian economy. Nevertheless, direct and indirect effects of reserve reproduction on social and economic development of oil-producing regions have been insufficiently assessed, even though it differs due to various macroeconomic processes and existing state mechanisms of subsoil use. The present paper examines the upstream sector of the petroleum industry comprising hydrocarbon exploration and production. The research hypothesis states that an imbalance in subsoil use results in growing inequality of socio-economic development of Russian regions, while the expansion of geological exploration work will reduce this effect. The study analyses the influence of geological exploration, leading to an increase in oil reserves and oil production, on gross regional product (GRP) per capita and personal income. For that purpose, the analysis was performed based on statistical data on five regions of the Russian Federation using the Cobb-Douglas production functions. According to the results obtained for blocks of the proposed regression model, Russian regions were divided into clusters in terms of the input effect on expected results. Overall, the influence of oil production on GRP per capita and average income is more significant compared to an increase in oil reserves. Moreover, the impact of the upstream sector in Tomsk oblast is stronger than in other constituent entities of the Russian Federation. The existing regional imbalance in social-economic development depends on not only available natural capital and tax relief system in subsoil management, but also differences in economic development and the role of petroleum industry in the analysed regions. In the context of recession, the expansion of geological exploration is required to increase natural capital that would provide the income many times higher than investments at the upswing of the cycle. The study results can be used for petroleum industry management in the field of geological exploration to justify the use of financial and fiscal incentives.

A strategy for improving export and import of Russian regions requires the identification of macroeconomic factors affecting their foreign trade. According to the scientific principle of deduction (from general to particular), trends observed in highly aggregated objects should be assessed first. Time series for foreign trade of the Siberian Federal District were analysed and compared with those of the Russian Federation, Central Federal District and the city of Moscow. Methods of comparative, structural, expert analysis, statistical estimation and econometric modelling are utilised in the research. The study demonstrates that the separation of profit centres and production sites through legal registration of company head offices (the mechanism called «administrative resource») negatively affects regional exports, as well as other aspects. 2018–2019 ratings of Russian regions in terms of production, volume of operations and gross regional product (GRP) per capita revealed the centre’s monopoly in the mining and manufacturing sectors, causing further centralisation of regional budgetary resources. Application of the method of stepwise regression based on partial correlations demonstrated the significant influence of world oil prices and the weak impact of sanctions for Russian trade. It was statistically confirmed that trade in the Siberian Federal District primarily depends on world metal prices, and then the rouble exchange rate, while the influence of the price of oil, whose export was practically taken out of the region, is quite weak. The proposed combination of profit centres with places of its generation is considered as an effective tool for regional equalisation of the foreign trade effect, aimed at overcoming the socio-economic heterogeneity of regions without involving the federal budget. The obtained results can be used by government bodies and research centres for developing regional strategies.

Recently, the Russian Far East has been receiving close attention from the government of the Russian Federation. Accelerated economic development of the Far Eastern regions requires trade intensification with foreign and domestic markets, which implies a reduction of various barriers. The study aims to assess the external and internal trade barriers of the Russian Far East using a consistent dataset and relevant econometric model for estimations. The assessment of trade barriers, expressed as values of the relative trade intensity and transport costs in the framework of modern gravity models, confirmed the trade bias of the Russian Far East in favour of the domestic market in the long term. High values of relative transport costs were offset by a high relative trade intensity between the Russian Far East and the domestic market. The conducted analysis shows that the reduction of external trade barriers between the Russian Far East and foreign markets can significantly increase their turnover. The obtained estimates revealed a trend of linking the regions of the Russian Far East to the domestic market due to the barrier reduction in the form of transport costs. This study can be further developed, as the presented methodology for qualitative assessment of internal and external barriers can be applied to analyse the costs of trade in commodity markets, to decompose export and import barriers, as well as to determine the potential for expanding regional trade with foreign countries.

A comparative assessment of business-to-company (B2C) e-commerce development in the Eurasian Economic Union (EAEU) countries is difficult to conduct due to the incommensurability of their economies and the lack of homogeneous data. To solve this problem, a composite index combining various sub-indices and indicators was created. The presented article discusses the creation of tools for assessing the B2C e-commerce development in the EAEU countries. The initial research data was gathered from reports of the International Telecommunication Union, UNESCO, the Universal Postal Union, the World Bank, as well as from official data of national statistical agencies and central (national) banks of the EAEU countries. The composite index was constructed by normalising the values of the indicators (method of normative ideals) for their comparison. Further, data values underwent a linear transformation to a 0 — 100 scale in order to ensure their proportionality. Weighting coefficients of the indicators were determined by the method of expert evaluations. Based on the developed index, countries may be ranked by the overall index, as well as by structural factors of B2C e-commerce readiness and use intensity. The use of the e-commerce development potential was analysed based on the values of individual sub-indices. In addition, the proposed toolkit can be applied to monitor changes in the EAEU indices over time, provided that the normalised values of the indicators are maintained. Policy makers can use the research results for improving the conditions for the e-commerce development in the EAEU member-states, as well as for creating a common space of e-commerce that contributes to the strengthening of economic integration. Moreover, the article contains methodological recommendations that can be utilised to create similar assessment tools for other regional economic blocs. The limitations of the study are related to the need to consider the regional specificity of the analysed countries or regions.

Russia’s transition to innovative development is required to ensure the sustainable competitive growth. At the same time, the share of the high-tech sector in innovation costs today is about 15 %. The study suggests ways to improve the system of innovation management in Russian regions. Analysis of modern theories on the organisation of regional innovation processes confirmed a hypothesis that innovation management should consider the regional innovation ecosystem as one of the key sustainable growth institutions. A proposed ecosystem approach states that regional innovation ecosystems in the context of globalisation depend on the coordinated goals of socio-economic and innovative development, differentiated approaches to their construction, sustainable flows of knowledge and technology, diversity and competition of participants. The research determined such priority directions of the state policy as the recognition of the lack of alternative to innovative development; creation of conditions for high-tech industries outside the established business structures; increase in budget research and development (R&D) expenditures; strengthening of self-organisation of science; stimulation of horizontal interactions between science and business. The presented differentiated approach to innovative strategies of Russian regions considers their production and technological specialisation, as well as the state of science and higher education. A described methodology for selecting the most promising regions for innovative transformations is based on a comparison of the values of the author’s indices for the development of scientific and educational space and high-tech industries. The calculations show that, in addition to Moscow, Moscow oblast and Saint Petersburg that are already at the centre of the country’s innovation system, regions occupying the first 10–15 positions in the constructed rating (Nizhny Novgorod, Sverdlovsk, Novosibirsk oblasts, Republic of Tatarstan, etc.) can also become local innovation centres. The obtained results can be used in the state innovation management of the constituent entities of the Russian Federation.

Nowadays, the influence of negative factors on the fiscal system has been strengthening at both the country and regional levels. In particular, income differentiation and fiscal capacity are increasing, inflation rate exceeds the target, negative trends of growing household debt and enterprise unprofitability are observed. Such factors are not fully considered by existing diagnostic methodologies for analysing fiscal and economic security indicators and threats. Thus, in order to adjust stabilisation decisions and implement relevant fiscal policies, it is necessary to update these approaches, especially in regions. The paper examines key definitions of threats and risks to regional fiscal security and presents the author’s classification of threats according to the incidence. Based on the analysed approaches to threat assessment and a proposed diagnostic mechanism, the research developed a method for diagnosing threats to regional fiscal security by bringing the actual values of indicators to standardised points. In addition, to determine the danger level of threats, indicator values were distributed by security zones. The suggested methodology, which includes 12 indicators, was used to analyse the fiscal security of the Komi Republic. As a result, significant threats to the regional fiscal security were identified in the economic, budget, tax, investment, innovation, price, banking, corporate and social spheres. Baseline data were obtained from Federal State Statistics Service, Federal Customs Service of Russia, Federal Taxation Service of Russia and the Bank of Russia. The proposed methodology is an effective diagnostic tool for analysing threats to fiscal security on the basis of important regional indicators. Federal and local authorities can use this particular method for monitoring regional fiscal systems.

Sustainability of regional budget revenues and the overall regional economic sustainability are mutually influential. The present research contributes to the identification of internal sources of budget sustainability observed in the constituent entities of the Russian Federation. The study proposed and tested an approach to distinguishing between steady growth rates of real revenues per capita of sub-federal budgets and their volatility using linear time regressions. The variance of the residuals is considered as an absolute measure of risk (instability), while the ratio of the residual standard deviation to the average income value is seen as a relative measure. Based on the construction of partial time regressions and use of variance rules, indicators of budget sustainability were decomposed according to income sources. The proposed methodology was applied to assess average real budget revenues per capita and determine steady growth rates, absolute and relative risks in 83 entities of the Russian Federation in 2010–2017. Budget systems of certain mining and border regions are characterised by low stability, while some highly diversified regional economies of the European Russia proved to be the most stable. In the group of tax revenues, the profit tax is the relative amplifier of budget risk, and the personal income tax is the risk damper. In the group of non-tax revenues, income from the sale of assets is the instability enhancer, and income from the use of property is seen as the damper. Among gratuitous receipts, subventions, followed by grants, play a stabilising role, while subsidies act as destabilisers. The dissimilarity between budget risk structures of the regional average and country portfolio, the most notable in the group of transfers, was explained by different time correlation of budget revenues in Russian regions. The proposed approaches can be improved by using non-linear regressions and appropriate methods for decomposing indicators of budget sustainability according to sources. The research findings can be used for the management of sustainable regional development and intergovernmental relations in the Russian Federation.

Stable political environment and prominent development of political institutions increase foreign direct investment flows by providing lower risks for investors. However, this impact can vary according to the development of the country. This study aims to investigate the impact of various indicators of political stability on foreign direct investment attraction for different economies distinguished by their development level. Our database includes 66 FDI-recipient countries and 98 FDI-investing countries for the period from 2001 to 2018. By applying the gravity approach and Poisson Pseudo Maximum Likelihood method with instrumental variables (IV PPML), we model bilateral FDI flows, incorporating variables reflecting various aspects of political stability formed by the principal components analysis. Interestingly, we found mixed results regarding the impact of political stability on FDI flows. In particular, political stability indicators were found to be insignificant, when analysing the bilateral FDI flows for the group of developed economies. We obtained similar result for the group of developing economies. However, political stability variables significantly influence FDI flows for countries with different development level, confirming the hypothesis that countries’ development affects bilateral FDI flows. Besides, we discover the significant difference between developed and developing countries referring to FDI-investors. Based on the obtained results, we highlight a few policy implications for developing and developed economies.

In order to ñover a more wide thematic audience of the journal Economy of Regiona, the authors Okrepilov V. V., Makarov V. L., Bakhtizin A. R., Kuzmina S.N. of the paper Application of Supercomputer Technologies for Simulation Of Socio-Economic Systems, published in the 2nd Issue, 2015 used the materials of previously published paper “Supercomputer Technologies Application in Social Sciences”, Economics and Mathematical Methods, Vol.49 (4), 2013 and “Supercomputer Technologies Application in Social Sciences”, UPRAVLENIE / MANAGEMENT (Russia), Issue 2, 2014 (DOI 10.12737/4167). The works used the same methods developed by the authors, but different results were obtained. A link to a previously published articles is included in the electronic version of the article Okrepilov V. V., Makarov V. L., Bakhtizin A. R., Kuzmina S.N. (2015). Application of Supercomputer Technologies for Simulation Of Socio-Economic Systems. Economy of Region [Economy of region], 2, 301-312