Showing papers in "Economy of region in 2022"

Analysis of the Digital Readiness and the Level of the ICT Development in Kazakhstan’s Regions

Abstract: The level of digital readiness and the application of information and communication technologies (ICT) are key factors of any innovation policy. This research has highlighted the development of analysis of the degree of digital readiness and assessment methods of digital transformations, which can be used at various levels of business management to formulate digital transformation strategies. The present study investigates the theoretical framework in the field of innovation and spatial development considering the impact of the level of ICT. The research was conducted using index and economic-statistical methods based on a systematic approach. We developed a methodological tool adapted to the regional management level. The ICT development index, Krugman localisation index and Herfindahl-Hirschman index were modified to analyse digital readiness and ICT development at the regional level. The algorithm includes the following steps: assessment of the internet usage level; analysis of the degree of costs for the production of ICT; evaluation of the digital literacy rate of the population; evaluation of the degree of regional industry specialisation in the field of ICT. It was revealed that Kazakhstan’s regions have varying levels of ICT development, which is why they have different prerequisites and prospects for digitalising their economy. The agglomerations that could become “growth poles” of Kazakhstan’s knowledge-based economy were identified, such as Almaty city, Nur-Sultan city, Karaganda, and Aktobe regions. Government bodies can use the research findings for Kazakhstani territories’ digital modernisation.

Comparative Analysis of Foreign Trade Development in the Digital Segment by World Regions

Abstract: Foreign trade, affected by digitalisation, acquired new features, while its development led to a new redistribution of world regions. The present article aims to reveal specific features and emerging trends in the digital segment of foreign trade and identify leading regions and success factors. In this case, the digital segment includes ICT-equipment and ICT-services trade. UNCTAD statistics for 2000–2019 were examined using the methodology of foreign trade structural and comparative analysis. We hypothesise that there are different development stages in the digital segment of foreign trade characterised by changes of leading regions. In particular, three waves in the development of the digital segment of foreign trade, corresponding to different characteristics, were identified. In the third wave, the growth rate of digital turnover remained the same but its share in the total global turnover decreased. It was revealed that the share of the digital segment is higher than the share of merchandise trade in the countries of one region. Asia-Pacific Region replaced the USA (that moved from the 1st place in the first wave to the 5th position) as the leading region. China, specialising in the export of ICT-equipment, came out on top with the 27.1 % share of digital exports in the country’s total exports, increasing by 15.9 times in 20 years. Russia, whose specialisation is the export of ICT-services, is closer to the end of the top 50 ranking of countries in this segment; its negative foreign trade balance was also revealed. The obtained findings can be useful for specialists developing the foreign digital trade strategy of Russia. In order to increase the potential of national economies, including Russia, in the digital segment of foreign trade, further research should focus on ways to prevent their lagging behind the leaders.

Uncovering New Economy Potential of Russian Regions on the Basis of the Last 20 Years Dynamics’ Analysis

Abstract: Recent global events have accelerated new technologies implementation worldwide. This process can likely lead to a future increase in regional disparities, especially in large developing countries such as Russia. Resource-based growth, which prevailed in the last 20 years in Russia, could slow down technological change in most regions. We aimed to assess regional potential for new economy formation based on its previous dynamics in 2000–2020. For that purpose, we developed a complex index that evaluates regional ability to create, use and disseminate new knowledge and technologies. There were long-term upward trends of most of the indicators in Russian regions due to intensive interregional alignment policy and a rapid spread of information and communication technologies. Economic growth, according to the Granger test results, contributed to the new economy formation. However, many research and development (R&D) indicators did not achieve higher values in comparison with 2000, when the oil prices started to grow. The growth rates in recent years have been low, and the share of R&D employees and R&D expenditures as well as entrepreneurial activity have declined especially in 2020. A significant but decreasing divide remains between leading and lagging regions. In accordance with the identified types of regions, it is necessary to pursue a diversified regional policy. Our results can be used to justify smart specialisation principles in Russia. Indirectly the study measures the resilience, or adaptability of regions to crises.

Key Directions of Agricultural Export Development in Russian Regions

Abstract: Steady growth of global demand for agricultural products provides opportunities for Russian economic development. Since the country’s considerable (but geographically heterogeneous) agricultural potential and government policies encourage import substitution and food exports, the main possibilities for agricultural export development should be explored considering regional differences. The present research substantiates the feasibility of agricultural export development, assesses regional export potential and offers recommendations on export-oriented development of regional agri-food industries. Criteria-based assessment and cluster analysis methods were applied. The study database includes quantitative indicators of agriculture and agri-food trade dynamics observed in Russian regions. At the first stage, analysis and generalisation of relevant publications, world experience and current trends allowed us to substantiate the feasibility of export-oriented development of the Russian agricultural sector. At the second stage, in order to assess export orientation, export openness and international involvement of regional agri-food markets, a methodology was proposed and tested on the Central Black Earth region data. At the third stage, a cluster approach was created to classify Russian regions and examine the potential of agricultural production and foreign trade of the agri-food market. The research proposes recommendations on the development of agricultural and food exports for the most prospective regions. The presented approaches and findings can be used in strategies and programmes for monitoring the export-oriented development of regional agricultural sectors. Future research can focus on methodological design for assessing and modelling the development of regional agri-food markets.

Economic Assessment of Regional Human Capital

Abstract: Sustainable regional development should consider the state and improvement of the quality of regional human capital. To this end, the present study focuses on economic assessment of human capital. Additionally, the research analyses the definitions of the “human capital” category, as well as approaches to identifying its composition and structure. After examining various economic assessment techniques, a definition of regional human capital was proposed. The cost approach was chosen as the most suitable tool for the economic assessment of human capital at the regional level. For economic valuation, the study uses a method developed by Chigoryaev and co-authors, including a number of theoretical and methodological modifications that take into account regional specificities. According to the assessment results, the total human capital in Kamchatka krai exceeded 191 billion roubles, of which more than 104 billion accounted for the fixed human capital. The constant growth of human capital in the period 2011–2018 was noted. Simultaneously, the share of the fixed human capital in the overall structure has been steadily increasing. The values of the chain growth rate of the operating human capital ranged from 1.0 to 1.06, while the values of this rate of the fixed human capital ranged from 1.14 to 2.05. A comparative analysis of the ratio of the total human and physical capital showed the presence of an imbalance: the share of human capital was gradually increasing and reached 37.5 % in 2018. The obtained results can be used to create strategic and programme documents in the field of regional socio-economic development. The modified method of Chigoryaev and co-authors can be applied for the valuation of regional human capital in other studies.

Using Computational Linguistics to Analyse Main Research Directions in Economy of Regions

Abstract: Over the past decades, the process of knowledge generation has accelerated, producing a lot of scientific publications, which makes reviewing even a relatively narrow subject area very demanding, if not impossible. However, recent text data mining tools can assist researchers in conducting such analysis in an objective and time-efficient way. We conduct such a literature review on 1307 articles published in the journal Economy of Regions from 2010 to 2021 using advanced topic modelling techniques. This analysis aims to describe the main research areas in the journal over time, the dynamics of their popularity and the relationship with key quantitative indicators. We identified 22 topics ranging from “Agriculture” and “Economic Geography” to “Fiscal Policy” and “Entrepreneurship”. We estimate how popularity of these topics was changing over time and find topics that gained the most popularity from 2010 to 2021 (+17.61 %, “Spatial Economics”) or lost it (-14.58 %, “Economics of Innovation”). The topic of environmental economics collects the largest number of citations per article (3.64, on average), and the topics on monetary policy and poverty are the most popular among manuscripts in English, which is also true for articles written by authors with foreign affiliation. Papers with third-party funding are concentrated the most in “Spatial Economics” (around 11 %), and the least — in “Agriculture”. Our results can help to understand the evolution in scope of research of Economy of Regions and serve researchers to find promising directions for future studies.

Assessment of the Socio-Ecological and Economic Welfare of the Russian Eastern Regions Using Sen’s Extended Function

Abstract: The accelerated development of the Russian Far East is among the country’s national priorities. Since the ultimate goal is to increase the well-being of the population, it is important to create a healthy environment. The article presents the comprehensive assessment results of the welfare of the Eastern regions in the context of achieving the strategic goals of the state policy for the development of the Russian Far East. The research aims to assess the character of socio-economic development, as well as to obtain quantitative characteristics of socio-ecological and economic well-being of the Eastern regions using a multiplicative model based on Sen’s extended welfare function. It is hypothesised that environmental factors play an important role in the quality of life in the Eastern regions, meaning that the inclusion of the corresponding component in the multiplicative model will lead to a decrease in the assessment of their welfare. For some regions, the study identified such negative trends as the strengthening of the raw material orientation of economic development, a decrease in the share of manufacturing industries, continuing resource export. The inclusion of the environmental component into the multiplicative model significantly affected the assessment results: in most of the Eastern regions, environmentally adjusted characteristic of regional development was significantly lower than the indicator that does not consider this aspect. Moreover, some border regions showed the worst dynamics of the examined indicators. Advantages of the border situation and accelerated development mechanisms currently implemented in the Far East have not yet contributed to a noticeable increase in the welfare of these regions. The research results can be used in the public administration practice for developing strategic planning documents, socio-economic and environmental programmes, as well as for evaluating the effectiveness of implemented accelerated development mechanisms.

Assessment of the Development of Competition in Regional Financial Services Markets

Abstract: Widely introduced competitive mechanisms (including in the financial services sector) require an assessment and measurement of the level of competition. Nowadays, the methods applied in practice are usually based on the calculation of indicators characterising market concentration. Simultaneously, little attention is paid to how consumers of services (represented by the population and business) assess the development of competition. Thus, the article presents a methodology for assessing the level of competition, which considers, among other things, the opinion of consumers. The methodology calculates a cumulative point score according to two groups of factors. The first group includes the so-called objective factors of competition development (independent of subjective opinion of consumers), while the other group presents subjective consumer assessments. The initial data for calculating the subjective component was gathered from population and business surveys. The assessment of objective factors is based on the materials of the Bank of Russia, as well as information published in open sources (financial reports of credit institutions, statistical databases of the Federal State Statistics Service, etc.). The proposed methodology was tested on various of regional financial markets: banking services, services of microfinance organisations, insurance. According to the obtained estimates, the examined markets can fall into one of three categories, namely, a market with developed competition, a market with insufficiently developed competition or a market with undeveloped competition. The calculation results show that the insurance market can be considered a market with developed competition in half of the analysed regions; the rest belongs to the category of markets with insufficiently developed competition. Based on the findings, it is possible to conduct a comparative analysis of the development of competition for individual markets and regions in general, as well as to examine relevant factors. In addition, objective competition and the development of competition noted by consumers of services can be compared.

Assessment of Product Localization during the Import Substitution in the Fuel and Energy Sector

Abstract: Considering the current geopolitical situation, the issues of technological sovereignty and fuel and energy sector development became urgent. In order to determine priorities for the implementation of public-private partnership (since these problems cannot be solved only through budgetary funding), areas largely depending on the import of equipment, technologies and software should be identified. The article presents a new methodology for assessing product localisation in the fuel and energy sector. The study reviews the existing approach (based on the Government Decree No. 719) and current challenges of implementing the local content policy in the Russian fuel and energy sector. The proposed methodology is based on the relevant experience of various countries in calculating the local content value, as well as the best practices of some Russian companies. Particular attention is paid to the complete value chain for products, services and software. The basic formula for calculating the product localisation includes estimations for each cost item in the value chain. Cost data taken from the appendix to the balance sheet, invoices and annual reports of enterprises were used as input. The total costs and import costs were considered for each cost item. According to the results of a comparative analysis of existing Russian and international methodologies, the developed approach was evaluated by the industry community and was considered to be the most relevant. The main risks of deploying the methodology in the import substitution programme, as well as risk management measures were described. The fuel and energy sector companies could use the research findings to assess the actual dependence on imported equipment and technologies.

Testing Unemployment Hysteresis with Multi-Factor Panel Unit Root: Evidence from OECD Countries

Abstract: Hysteresis is a dominant feature of unemployment in numerous countries. According to the hysteresis hypothesis, it is a well-known fact that high unemployment may persist and remain an economic threat in the long run if policy measures are not taken. In this study, it is tested whether the unemployment rates for 10 selected countries of the Organisation for Economic Co-operation and Development (OECD) (Belgium, Canada, Czech Republic, Estonia, France, Japan, Netherlands, Spain, Britain and the USA) contain unit root or not, in other words, whether the hysteresis effect is valid for these countries. For this purpose, this study utilises the concept of the multi-factor panel unit root test proposed by Pesaran, Smith and Yamagata. This method measures cross-section dependence through factors. The test analyses whether the unit root is valid or not, using information about a sufficient number of additional explanatory variables. The characteristic of these additional variables is that they must share a common factor with the variable whose stationarity is tested. It is accepted that this common factor causes cross-sectional dependence. We have taken tax wedge, trade union density and minimum wage as factors that cause cross-sectional dependency and affect unemployment hysteresis. In this test developed by the authors, in the case of a multi-factor error structure, the test procedure is completed by using the information contained in 3 additional variables. The study explores not only the validity of unemployment hysteresis but also the factors that affect the rigidity of the unemployment rate. However, the research was unable to encompass the entire OECD countries and all times because of the lack of data. The results showed that the hysteresis is valid for 10 selected OECD countries.

Identification of Industrial and Innovative Development Models of Regional Economic Systems

Abstract: New industrialisation challenges, turbulent economic environment and opening market niches change the structure of competitiveness factors and determine the innovativeness of industrial development. In the current context, it is necessary to deepen the analysis of industrialisation and innovation performance of regions. Therefore, this study aims to identify industrial and innovative development models present in Russian regions. To this end, we propose a methodology based on assessing the localisation coefficients of both regional industrialisation and innovation performance. Calculation of these indicators resulted in the creation of four models: Model 1 (low industrial development and low innovation performance), Model 2 (low industrial development and high innovation performance), Model 3 (high industrial development and high innovation performance), Model 4 (high industrial development and low innovation performance). The classification of the constituent entities of the Russian Federation according to the industrial and innovative development model shows that more than 40 % of regions use Model 1 and about 12 % of territories use Model 2. Simultaneously, approximately 27 % of regions (including Tula, Lipetsk, Chelyabinsk, Vladimir oblasts, Republic of Bashkortostan) chose Model 3, which most fully meets the new industrialisation challenges. The high stability of this disproportionate structure indicates the absence of positive dynamics and poor balance of industrial and innovation policy measures in most Russian regions in the period 2015–2019. The study results can be used to create an alternative ranking of innovative development of regions. Further research can apply these findings to assess the efficiency of regional industrial and innovation policies.

Export of Medical Devices and Industry Integration of Russian Regions in the Context of Covid-19

Abstract: The sudden and severe outbreak of Covid-19 has both challenged the world economy and created new opportunities to address the problem of domestic production, integration and export growth in Russia. The study aims to identify the characteristics of medical exports and assess the integration of individual Russian regions in the context of a pandemic. To this end, the paper analyses the volume and geography of export transactions of 40 Russian regions exporting medical devices to prevent the spread of new coronavirus infections. Characteristics of medical exports and sectoral integration in conditions of pandemic risks were identified. For example, exports of Covid-19 medical devices are highly concentrated in a small number of Russian regions. The development of export-oriented medical devices accelerated due to the intensification of existing production capacities as well as the involvement of related sectors in the value chain. Additionally, non-economic factors (threats to life and health of nations) are becoming increasingly important in international trade in the short term. The Eurasian Economic Union demonstrates its growing significance as a regulator of medical device supply within the integration area. The research highlights the high adaptation of Russian local producers to the needs of the world and domestic economy. Moreover, an increase in exports simultaneously allowed Russia to satisfy the domestic demand for medical devices for preventing and controlling the spread of coronavirus. The sector development requires the strengthening of export support institutions both in the major regions exporting Covid-19 medical devices and in the regions where this industry is still in its infancy but has already shown steady growth. Future research can focus on studying export trends of medical devices in the face of viral risks, as well as expanding the context to include strategies for the integration of Russian regions into global economic relations, considering sectoral specificities and the geostrategic situation.

Assessment of Export-Led Growth Hypothesis: The Case of Bangladesh, China, India and Myanmar

Abstract: The Asian countries, particularly Bangladesh, China, India and Myanmar, have been witnessing impressive economic growth rates due to their trade performance in the international market. Although export-led growth assumption is functional in these economies, existing pieces of literature hardly considered them in their studies. Against this backdrop, the present study investigates the export-led growth hypothesis for four South Asian countries — Bangladesh, China, India, and Myanmar — covering country-specific different time ranges. This research employs the autoregressive distributed lag (ARDL) bounds testing approach to co-integration and the MWALD Granger causality test to determine the causal relationship between variables. The results obtained from the autoregressive distributed lag method confirm the co-integration among the variables. In addition, the Granger causality test explores both the export-led and growth-led export hypotheses in Bangladesh and India as per the bidirectional causation between exports and economic development. Only the export-led growth theorem is relevant to China, and the growth-led export hypothesis is valid in the case of Myanmar based on the unidirectional causation between these variables. Therefore, any joint footstep of BCIM countries is critical to promoting exports by penetrating new destinations with diversified export goods and services. The obtained findings also indicate the potential for utilising these countries’ unused resources to encourage exports to uplift the existing growth trajectory.

Impact of Universal Basic Income on Employment According to Russian Experts

Abstract: The issue of universal basic income (UBI) has been gaining importance due to the growth of precarious employment, unemployment and inequality in the context of the development of digital technologies, especially considering the COVID-19 pandemic and its consequences. The article first presents the generalised and systemised reasoned opinions of Russian experts on UBI in order to examine its potential impact on employment. The initial research data resulted from a survey of different groups of Russian experts conducted by the authors. This information was supplemented by the results of various mass surveys. It was revealed that a significant part of Russian experts have concerns that UBI can negatively affect work incentives and labour supply. The systematisation of expert assessments allowed the research to create scenarios of the potential impact of UBI on population employment and work incentives, formal and informal employment, the ratio between paid and unpaid work, working and free time, the quality of leisure time. The study findings can be used as information and analytical support for the state policies aimed at improving the level and quality of life of the population, as well as making decisions on the appropriateness of UBI tools (including in Russia). Future research will examine in detail the impact of universal basic income on the labour market parameters, taking into account socio-demographic factors.

Simulation of Residential Real Estate Markets in the Largest Russian Cities

Abstract: The existing mass appraisal models and mathematical tools for predicting the market value of residential property have a number of disadvantages, as they are developed for individual regions. Without considering the constantly changing economic environment, these models quickly become outdated and require constant updating. Thus, they are not suitable for construction business optimisation. The study aims to create a universally applicable real estate appraisal system for Russian cities, regardless of the constantly changing economic situation. This goal was achieved through the creation of a neural network, whose input parameters include construction and operational data, geographical factors, time effect, as well as a number of indicators characterising the economic situation in specific regions, Russia and the world. In order to examine the dynamics of real estate markets in the Russian Federation, statistical data for neural network training were collected over a long period from 2006 to 2020. Virtual computer experiments were performed for testing the developed system. They showed that minimum size one-room apartments of 16 square meters have the highest unit cost per square meter in Moscow. Two-room apartments with an area of 90 square meters have the maximum price, as well as 100 sq. m. three-room, 110 sq. m. four-room and 120 sq. m. five-room apartments. In Ekaterinburg, two-room apartments with a total area of 30 square meters have the highest cost per square meter; the same applies for 110 sq. m. three-room, 130 sq. m. four-room and 150 sq. m. five-room apartment. Thus, the proposed system can be used to optimise the construction business. It can be also be useful for government institutions concerned with urban real estate market management, property taxation, and housing market improvement.

Methods for Evaluation of the Region’s Needs for Human Resources based on Statistics and Patent Landscapes

Abstract: Implementation of a new technological platform in Russia requires providing promising areas of professional qualification with human resources. Post-pandemic structural economic transformation has accelerated changes in the labour market and highlighted the need to develop new approaches and forecasting methods with the priorities of regional technological development. The study presents a methodology to reveal the regional demand for staffing based on the analysis of the factors affecting staff demands using structured and unstructured datasets. The study is focused on forecasting the region’s needs for human resources based on data mining and patent landscapes. That forecasting should consider the economic focus of a region as well as its location, investment and R&D development programme, labour market specificity. The advantage of the proposed methodology is obtaining reasonable estimates of the region’s needs for human resources with data mining and patent landscaping methods in conditions of limited official statistical data. Our database includes more than 25 million records: full-text collections of Russian and foreign patents, research papers, statistical indicators, etc. As a result, we identified promising training areas attractive for qualified personnel in the Vologda region corresponding with the priorities of regional technological development. The future development of this research is the improvement of the methodology for quantitative assessment of the regional need for professionals in particular industries. The obtained results can be useful to government bodies and research centres for the development of regional strategies.

Effects and Risks of Digital Quality of Life in Russian Regions

Abstract: Widespread digital transformation significantly changed people’s quality of life. We hypothesise that the digital component of people’s quality of life had a positive but differential impact on economic growth in Russian regions during 2015–2019. Moreover, economic and institutional risks occurring at the current stage of digital transformation could negatively affect economic development. The research pays special attention to the institutional factor, namely, project management quality and its influence on real gross domestic product (GDP) per capita in Russian regions. Methods of economic research were used such as index, rating, expert evaluation methods as well as regression and panel data models (including those with dummy variables). Transformation assessment was based on an integral index proposed by the authors called the Russian regional index of digital component of people’s quality of life (RRIDCPQL). The value of this digital index was increasing during 2015– 2019. The hypotheses of statistically significant influence of the digital quality of life, regional and temporal unobserved factors on real GDP per capita in 2015–2019 were confirmed. However, the study rejected the hypotheses of the positive impact of digitalisation on the unemployment rate and on the decrease in the share of government employees. Positive influence of digitalisation on the divorce rate was revealed while its negative influence on economic criminality and real income per capita of the population was partially confirmed. The importance of project management quality of the program “Digital economy of the Russian Federation” for regional development was demonstrated. The research results presenting new data on the growth of digital economy can be used to adjust the implementation of digital projects in Russian regions.

Electricity Consumption Growth in Russian Regions as a Factor of Their Socio-Economic Development

Abstract: The indicator of specific (per capita) electricity consumption (SEC) is stabilising in developed countries and increasing in developing economies. At least since the mid-2000s, the difference between the two groups of countries in terms of available power has been decreasing. In contrast to this trend, the transition of Russia to a market economy is characterised by the divergence of regions in terms of SEC. SEC of regions, being on average similar to that of the Netherlands, France, Germany, Great Britain, began to differ by 20 times. The technocenosis theory shows the need to change this negative trend. The low electricity consumption of developing countries depends on their inability to increase its production. In Russia, the problem is due to the low potential of the consumption sector, primarily in regions with SEC below 4 MWh/person per year. The solution of this macroeconomic problem, namely, the reduction of the existing differentiation in regional specific electricity consumption will help maintain the structural stability of the Russian economy and ensure its functioning in the context of external environment changes. Creation of conditions for the energy consumption development in industrial and agricultural enterprises is not a sectoral task of the electric power industry. Considering the sanctions imposed on Russia, structural stability of the national economy can be increased by improving the investment climate resulting from a decline in electricity prices for new non-residential consumers in regions with SEC below the level of developing countries. For these subsidy depending “outsider” regions, an increase in the availability of electricity, rather than the construction of new energy facilities, stimulates the labour productivity growth, re-industrialisation, and emergence of growth points.

Factors of Export Diversification: Empirical Analysis of Russian Industrial Regions

Abstract: Oil and gas dependence and the volatility of their prices is currently a serious challenge for the Russian economy. Coincidently, export revenues from oil and gas products are the main source of the federal budget. Export diversification can contribute to risk reduction for the Russian economy by increasing the share of products from other industries in the export structure. In this regard, the present study examines the determinants of export diversification in Russian industrial regions using econometric modelling methods. To this end, the Herfindahl and Theil indices for 97 export groups were calculated. It is hypothesised that the development of small and medium-sized enterprises, as well as the sanctions imposed by Western states against Russia are the main factors of export diversification in industrial regions. Simultaneously, natural resource extraction is assumed to significantly increase the concentration of exports in the regions. To test this hypothesis, panel data of 50 Russian industrial regions for the period 2001-2019 were analysed. The quantile regression approach was applied to solve the heteroscedasticity problem. Three groups of regions were distinguished according to their level of diversification: regions with a high level of export diversification (Q10-Q30), with an average level of diversification (Q40-Q60), with a low level of export diversification (Q70-Q90). The research findings show that the development of small and medium-sized enterprises contributes to export diversification in Russian industrial regions. While the sanctions did not have a significant impact on export diversification, regional potential and natural resource extraction increase the concentration of exports. The obtained study results complement the existing literature on export diversification in Russia, and contribute to the development of policy implications.

Demographic Research in the Context of Economic Development and Security of Regions

Abstract: The present paper reviews the scientific research on key global demographic megatrends such as population ageing and migration that have a significant long-term impact on social and economic development. However, attitudes towards these demographic trends and their consequences range from seeing them as security threats to development opportunities. This review systematises demographic studies and identifies the most promising scientific areas to explain a wide range of consequences and propose relevant recommendations. Thus, a research algorithm was constructed in order to complete the following three tasks: (1) to analyse and classify the consequences of the described demographic trends for social and economic development; (2) to conduct a comparative analysis of such sources of filling the labour shortage in Russian regions as stimulating labour participation of pensioners and facilitating the access of foreigners to the labour market; (3) to identify literature gaps that require further attention. To create a database, keywords «population ageing» and «population migration» were searched in the main collections of Web of Science, Scopus and Russian Index Science Citation (RISC). The survey showed that ageing and migration do not hinder economic growth and well-being of the population. However, these demographic processes require effective policy development to comprehensively solve economic and social issues, as well as the problems of the elderly population and migrants. Therefore, ageing and migration should rather be seen as opportunities for territorial development, while poor adaptability of existing institutions to these processes is what threatens economic security. The conducted study shows that the problem of institutions’ adaptation to modern demographic trends is not fully examined in scientific literature and requires further investigation.

Improving the Ranking of Russian Smart Cities

Abstract: Digitalisation and urbanisation have led to smart city becoming a key element of the concept of sustainable development, acting as an object of sustainable development management. Thus, a smart city must become a sustainable smart city. The first step is the creation of the system of current state diagnostics or smart city ranking. This ranking should consider international standards, the specificity of Russian urban development, as well as various components of sustainable development. It is hypothesised that the ranking methodology reflecting these components can be used to analyse the dynamics of sustainable development based on the chosen criteria and factors. To assess social, environmental, economic and management components of cities with a population of more than 100,000 people, the proposed technique relies on the theory of multiple comparisons and the distance method. The comprehensive assessment of smart cities includes 71 indicators grouped into 8 criteria: people, social cohesion, economy, management, ecology and the environment, transport, urban planning, technology. The study analysed Russian and international statistical databases, as well as data from industry agencies. The ranking of 171 cities was developed; regional features of Russian smart cities were identified using the selected criteria. The cities of Moscow, St. Petersburg, Balashikha, Krasnodar and Kazan are at the top of the ranking. The leadership of the Central Federal District and a significant differentiation by the criteria “urban planning” and “technology” are the key regional features. Annual comprehensive assessment can be used to track the dynamics of the development of smart cities, evaluate the effectiveness of decision-making and implementation, plan urban development based on federal and regional digitalisation projects, as well as create strategies to enhance the sustainability of Russian smart cities.

University and Regional Landscape of Doctoral Studies in Russia: Financial Trajectories of Graduate Students

Abstract: Training of a new generation of graduate students plays a key role in ensuring a country’s sustainable socio-economic development and active enhancement of human capital by continuous reproduction of cutting-edge knowledge in the form of research and development (R&D) for industry. In this context, it becomes important to examine the development dynamics of doctoral studies in Russian regions, as well as the graduate students’ financial well-being affecting their educational mobility and general opportunities to receive education (in particular, necessity of employment). The development of doctoral studies is analysed taking into account the distribution of resources (financial, intellectual) by regions and universities. The study also considers the concentration of resources in Russian universities capable of generating breakthrough ideas and technologies, which can be seen as centres of attraction for proactive youth. The methods of secondary data analysis, comparison, classification, and infographics were applied to process information. Such data as the monitoring of the effectiveness of Russian universities in 2014-2020 and sociological surveys of graduate students of a leading Russian university for 2017-2020 were analysed. As a result, the study presents a map showing the concentration of graduate students in certain regions, which takes into consideration their number, inflow and outflow. In addition to the capital regions (their share is 47.9 %), the Republic of Tatarstan (3.2 %), Tomsk oblast (2.4 %) and Sverdlovsk oblast (2.1 %), where leading Russian universities are located, were revealed to be the centres for attraction of graduate students. The top 7 regions also include Belgorod (the share of graduate students is 2.7 %) and Rostov oblasts (2.4 %) characterised by the presence of strong research and federal universities. However, due to the lack of funding (85 % of graduate students have to combine work and studies), the outflow to foreign universities is increasing even in the regions that attract a large number of scholars. The obtained findings can be used to improve the mechanisms for supporting graduate students in order to contribute to sustainable development of regions.

Development of Methods for Assessing the Digital Maturity of Organisations Considering the Regional Aspect

Abstract: Digital transformation has reached all regions of the Russian Federation. In this regard, it is essential to assess the digital maturity of various companies. Simultaneously, digital transformation projects should take into account interregional imbalances and regional specificities. The present study aims to develop an economic tool for assessing the digital maturity of organisations considering the regional aspect. To achieve this goal, we analysed theoretical approaches to assessing the digital maturity, presented a system of indicators that consider regional aspects, and created an assessment algorithm for interpreting the results. The developed economic tool allows the assessment of internal and external digital maturity in terms of quantitative indicators. Internal digital maturity considers scientific and technical, as well as production factors. In the presented methodology, external digital maturity considers four regional aspects: human, financial, consumer, infrastructural. Digital maturity was calculated using data normalisation methods to ensure their commensurability and analytic hierarchy process to consider the weight of each factor. Based on the presented scale, obtained via the method of simple grouping into equal intervals, digital maturity of organisations can be classified as basic, emerging, medium, advanced or high. Additionally, the conducted assessment of digital maturity allowed us to identify the “bottlenecks” in organisations that should be eliminated in order to increase the effectiveness of digital transformation. The developed economic tool was tested on the example of high-tech enterprises of the Russian Federation. The relationship between the calculated estimates and digital development of Russian regions was demonstrated. The obtained results can be used to implement strategies for managing the digital transformation of organisations, as well as to develop regional policies.

Optimal Spatial Models of Interregional Economic Cooperation in the Field of Innovative Economy

Abstract: Domestic cooperation of companies in the field of innovative economy seems to be a promising research area in Russia, especially considering recent macroeconomic events caused by sanctions, in particular, restrictions on the import of high-tech goods. Thus, the present study examines the optimal spatial scale of interregional innovation cooperation. The article presents an analysis of approaches to determining the optimal number of k-matrices of relations between innovation active regions. It is hypothesised that the innovative activity of the business sector in one region does not influence the innovative activity of its neighbours and vice versa. Stepwise regression was applied to identify the core explanatory variable. Based on the spatial weights matrices, a spatial econometric model was constructed using the least squares method. Further, the global Moran’s I was employed to test the spatial correlation, in particular, local indicators of spatial association (LISA) using the queen criterion of contiguity were utilised to determine the dependencies of innovative activity between neighbouring regions. The analysis used panel data from all Russian regions for the period from 2010 to 2019, as well as spatial econometric modelling to identify the side effects of the optimal spatial scale. As a result, the study revealed the presence of spatial correlation in the levels of regional innovative activity, the size of markets, as well as institutional support for enterprises in individual regions. Additionally, the research identified factors positively affecting the scale of innovative activity of the regions and adjacent territories, such as regional domestic income, the number of participants in innovation processes and infrastructure facilities. It has been established that the neighbourhood of regions characterised by the presence of many participants in innovation processes (at least 100 units), as well as innovation infrastructure facilities (at least 810 units) will be seen as the optimal scale of regional cooperation.

Increasing the Volume of Agro-Industrial Production to Ensure Food Security and Increase the Export Potential of the Russian Agricultural Sector

Abstract: Currently, the Russian agricultural sector aims to simultaneously achieve two priority goals: to ensure import substitution (or the country’s food security, taking into account rational consumption standards) and to increase exports of agricultural products and food. In this regard, the present study develops proposals for improving agricultural policy and linking these two tasks. The study analysed existing normative legal documents in the field of agricultural policy management and agricultural exports development, relevant foreign experience, as well as Russian and international statistics. It was revealed that an increase in agricultural food production and in the mass of commodities led to export growth. As a result, the negative balance of foreign trade in food decreased, and Russia became a net exporter in 2020-2021. The structure of agri-food exports was examined in order to identify the export potential. Approximately 1/3 of exported goods belong to the group of low-processed products, while only 15 % are highly processed products, which are characterised by a significant negative balance. Competitiveness of products, which plays the most important role in increasing exports, requires the development and implementation of domestic advanced scientific and technological solutions. According to the competitiveness assessment, Russia is a competitive supplier of a wide range of agri-food products, since the prices offered by Russian farmers and exporters are lower or comparable to the prices of major global exporters. Since export growth depends on an increase in agricultural food production, production growth opportunities were considered. The analysis of the consumer purchasing power and food consumption demonstrated their significant differentiation, both by decile groups and by place of residence. The presented findings can be used to improve agricultural policy and adjust state support for the agricultural industry aimed at its effective development.

Роль человеческого капитала в цифровой экономике на институциональном и региональном уровнях

Abstract: The present article examines the role of human capital in Russia’s transition to a digital economy. In this context, it is necessary to establish new models of the functioning and development of the Russian national economy and increase digital literacy among the general population. We hypothesise that human capital plays an important role in the process of digitalisation of state institutions and commercial companies. Particular attention is paid to the effect of introducing mechanisms to support and promote private capital to advance regional development. The research aims to highlight the role of human capital as a driver of the national and regional economy in the transition to the post-industrial state. To this end, the following objectives were achieved: parameters of the sapio-economic system were identified, the obtained results were interpreted; the experience of public and private institutions in creating conditions for innovative development of human capital was analysed (both in private sectors and in social institutions). The research methodology includes various scientific methods — induction, deduction, abstraction — as well as econometric analysis techniques. The study reveals indicators of interdependence between human capital development and regional socio-economic growth. As a result, the paper described the tasks of educational institutions focused on developing necessary skills to ensure the operation of digital systems. Additionally, the research identified ways to advance the development of the domestic digital environment, including through the creation of personnel forecasting practices for high-tech and knowledge-intensive industries. Recommendations for the successful implementation of long-term programmes for innovative development of the digital environment were given. Thus, the conducted analysis confirmed the hypothesis that human capital is a necessary condition for the development of knowledge-intensive industries and an important factor in the creation of regional value added and formation of the gross regional product.

Configuration of Regional Entrepreneurial Ecosystems through the Prism of Spatial and Hierarchical Analysis

Abstract: Nowadays, entrepreneurship should be analysed from the perspective of interconnectedness and mutual influence of elements of regional economic systems, since the type and intensity of their interaction determine the emergence of windows of opportunity for entrepreneurs. Thus, the present study uses an ecosystem approach. We hypothesise that the spatial configuration of the performance of regional entrepreneurial ecosystems (REES) largely depends on the interaction between local entrepreneurial ecosystems, as well as on the cumulative impact of REES on local entrepreneurial ecosystems. Using the methodology of spatial and hierarchical analysis, the study investigates the dependence of the development of local entrepreneurial ecosystems on their embeddedness in regional entrepreneurial ecosystems, assesses the spatial connectivity of REES, and considers relationships between small and large businesses in regional entrepreneurial ecosystems. The global Moran’s I and the Getis-Ord statistics for regional entrepreneurial ecosystems used to assess their spatial connectivity were calculated based on the analysis of data concerning the shipping volume of large and medium enterprises from 2315 municipalities of 85 constituent entities of the Russian Federation. At the level of local entrepreneurial ecosystems, the study revealed the link between the variation in the values of the shipping volume of business entities and their belonging to specific regional entrepreneurial ecosystems (constituent entities of the Russian Federation). In addition, a positive relationship was found between the shipping volume of large and medium enterprises operating in local entrepreneurial ecosystems, the shipping volume of goods produced by small enterprises and the average revenue of individual entrepreneurs. Considering the identified factors of spatial determination of regional entrepreneurial ecosystems and the closeness of interregional and intermunicipal ties of local entrepreneurial ecosystems, it is possible to generalise the best practices of spatial organisation of regional business communities and create effective development models.

Inequality of Opportunity in Russian Regions: Objective Estimates and Population Perception

Abstract: Income inequality driven by inequality of opportunity can lead to slower economic growth and social instability. The present paper analyses inequality of opportunity in three Russian regions, namely, Moscow, Stavropol krai and Chelyabinsk oblast. For each region, the contribution of unequal opportunities to income inequality (objective estimates), as well as the population perception of inequality of opportunity (subjective estimates) were examined. The existing estimates of inequality of opportunities in Russia at the regional and national levels were compared. Additionally, the correspondence between the subjective perception of inequality of opportunities by the population of the region and its objective estimates was considered. The research is based on the data of а sociological survey conducted by the Russian Presidential Academy of National Economy and Public Administration in 2019. Methods ensuring the comparability of the obtained estimates with the results presented in the works of Russian and foreign scientists were utilised. The contribution of inequality of opportunity at the regional level ranges from 9 to 12 % for labour income and from 7 to 13 % for average per capita income; these values are considerably lower than the national estimates reported in earlier studies. This situation can be explained, among other things, by significant interregional inequality in Russia. The composite index of subjective inequality of opportunities, constructed in accordance with people’s perception of various success factors, shows that 14–20 % of the population in the above regions consider the problem of inequality of opportunity as important or very important, and 6–11 % as very important. The conducted regression analysis shows that higher levels of education and well-being correspond to less acute perception of inequality of opportunity. No significant regional differences were found, since the perception of inequality mostly depends on individual characteristics of the respondents rather than on their place of residence. The considerable difference between the objective estimates of regional inequality of opportunity and its perception is consistent with the results of international studies. For example, the perception of inequality of opportunity in Stavropol krai is higher than in other regions, while its objective estimate, on the contrary, is lower. To form a complete picture of inequality of opportunity in Russian regions, it is necessary to conduct a survey designed to be representative at the regional level.

Institutional Infrastructure of Arctic Spatial-Economic Units

Abstract: An important problem of the impact of institutional infrastructure on the decomposition and spatial development transformation of regions of various hierarchical ranks, including the Arctic zone that is divided between the Arctic countries according to the national principle, is insufficiently studied. The majority of scientific works devoted to this issue mostly focus on the traditional economic assessment of the sectoral effect of activities and the concept of spatial economics. Thus, methodological approaches to the study of infrastructure and institutional structure should not rely on the traditional principles of mainstream economics. Instead, they should be based on the system-evolutionary model of modern natural science and should be closely related to such an indicator of system development as self-organisation. Internal (endogenous) and external (exogenous) elements of infrastructure cause stability (order) and chaos (disorder) in the development of systems, as well as lead to the interrelated and balanced formation of hierarchical and heterarchical organisational models of regional spatial units. This methodological approach also applies to institutional infrastructure. The present study provides theoretical justifications and methodological approaches corresponding with the aforementioned principles of infrastructure research, designed for the regions of the Arctic basin. In terms of scientific practice, it is proved that the intensification of institutional infrastructure in the Pacific Arctic depends on the creation of the Russian-American Bering/Pacific-Arctic Council (BPAC). Various expert communities discussed these proposals at several international conferences. At present, however, their practical implementation became impossible due to complicated geopolitical situation. Despite this, it is necessary to continue research aimed at the improvement of institutional structures and coordination of interactions between the Arctic regions, especially in cross-border areas of neighbouring countries. The obtained findings will definitely be useful for the Arctic community, when a reasonable approach to this problem will again prevail over geopolitical disputes.

Characteristics of Population Reproduction in the Ural North

Abstract: Numerous studies have been examining the influence of coronavirus on economic and demographic indicators of various countries and regions in the period from 2020 to 2021. However, little attention is paid to the consequences of the Covid-19 pandemic for Northern and Arctic regions. The present study aims to identify the characteristics of population reproduction in the northern oil and gas regions and consider factors affecting the morbidity and mortality from Covid-19 in the post-Soviet and coronavirus periods. In particular, Khanty-Mansi Autonomous Okrug — Yugra (KhMAO) and Yamalo-Nenets Autonomous Okrug (YaNAO), the Northern and Arctic regions of the Ural Federal District, were examined. The impact of the pandemic on population reproduction in the Ural North was assessed taking into account the regional demographic potential. To this end, the methods of retrospective and statistical analysis, aggregation, grouping, averaging and analogy approaches were utilised. The conducted retrospective analysis revealed the dependence of demographic processes on the time of settlement and development of the territory. In most regions and subregions of the Russian North and Arctic, with the exception of KhMAO and YaNAO, a gradual decrease in the population was observed. In 2020, mortality among patients with Covid-19 in the Ural North was lower than the national average, while the proportion of infected people to total population, on the contrary, was higher. This can be explained by the lower proportion of elderly in Yugra and YaNAO compared to other Russian regions. The research demonstrated that the mortality and birth rates in the most reproductive groups (people aged 20-29 and 30-39) were not affected by the Covid-19 pandemic. The main risk group is the older population aged 60-65 and over, determining the rate and number of deaths from coronavirus. The statistical analysis confirmed the existence of an eight-month cycle of Covid-19 waves from the lowest point to the peak. Future studies will focus on assessing the consequences of the pandemic for the population of the Arctic region at the municipal level.