scholarly journals Spatial-territorial factors of economic growth in the Russian Federation

R-Economy ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 42-51
Author(s):  
Rustem R. Akhunov ◽  
◽  
Azat V. Yangirov ◽  
Keyword(s):  
Economic Growth ◽  
Russian Federation ◽  
Growth Rates ◽  
Value Added ◽  
Retail Trade ◽  
Economic Research ◽  
Russian Regions ◽  
Economic Activities ◽  
National Economic ◽  
The Russian Federation

Relevance. In contemporary economic research, the study of the diversity of factors of national economic growth is gaining more and more significance, particularly with regard to the so-called 'spatial-territorial factors'. In contrast to the existing concepts of regional and spatial economy, the approach described in this paper is based on the hypothesis that it is possible to accelerate national economic growth. It can be done by stimulating extended economic reproduction on the subnational level, that is, on the level of relatively independent and self-contained spatial and administrative units such as regions of the Russian Federation, municipalities, agglomerations, etc. Research objective. The study aims to propose a decomposition of the economic growth rates in Russia by territorial units and to describe the spatial-territorial factors of national economic growth. Data and methods. To characterize the spatial-territorial factors, we used indices of the physical volume of gross regional product (GRP) and gross value added (GVA) in types of economic activities in Russian regions in percentage to the previous year for the period of 2013-2018. The types of economic activities were specified according to the Russian Classifier of Economic Activities of 2007 (OKVED) (Statistical Classification of Economic Activities in the European Community - NACE Rev. 1.1 (2013-2016)) and OKVED-2 (NACE Rev.2 (2017-2018)). Results. We estimated the contributions of Russian regions to national economic growth by analyzing the data on the key types of economic activities in a 6-year period (2013-2018). We also identified the regions which accounted for the largest losses in economic growth, on the one hand, and those which, on the other hand, acted as drivers of the country's economic development. Conclusion. There is a small number of regions lagging in terms of GRP and their influence on the national rates of economic growth is also insignificant. The general rates of GRP decline in a region are determined, first and foremost, by the sluggish growth in those types of economic activities that have the largest share in GRP. The number and share of the regions which demonstrate extended economic reproduction, that is, deliver at least 2% growth a year, are also quite small. These regions make up slightly more than 19% of the country's GRP. The largest group of regions comprises those regions that do not go beyond the simple reproduction (their growth rates are less than 2% a year), while their share in the country's GRP exceeds 74%. The so-called ‘heavyweights’ - regions accounting for the largest share in the country's total GRP - have the strongest effect on the national rates of economic growth, hindering it. It is the economic structure of these regions that has the biggest influence on the country's performance in such types of economic activities as wholesale and retail trade and maintenance and repair of motor vehicles. Sadly, it is in these sectors that the 'heavyweights' demonstrate the largest losses in GVA. As a result, these sectors suffer the most, which is bound to be reflected in the country's overall economic growth.

scholarly journals Phenomenon of Structural-Technological Proximity and Knowledge Spillovers between Russian Regions

2020 ◽  
Vol 16 ◽  
pp. 1254-1271
Author(s):  
Galina A. Untura ◽  
Maria A. Kaneva ◽  
Olga N. Moroshkina
Keyword(s):  
Economic Growth ◽  
Russian Federation ◽  
Knowledge Spillovers ◽  
Knowledge Spillover ◽  
Spatial Proximity ◽  
Russian Regions ◽  
Economic Activities ◽  
Novosibirsk Region ◽  
The Russian Federation ◽  
The Impact

International theoretical and empirical studies have shown that regional development and economic growth largely depend on spatial and non-spatial proximity of regions, which generates knowledge spillovers. We developed a methodological approach to measuring and visualising spatial and structural-technological proximity affecting regional knowledge spillovers. Moreover, we tested the techniques of the cartographic visualisation of the proximity of Russian regions. Further, we analysed foreign and domestic approaches to studying spatial and non-spatial proximity and obtained new results. We described the stages constituting a methodology for the quantitative assessment of different types of regional proximity. Additionally, we proposed a method for constructing a typology of regions based on the coefficients of the non-spatial proximity matrix, calculated according to the indicator “gross value added” for 15 sectors of the Russian National Classifier of Economic Activities (OKVED) for Russian regions. Using the data for the Novosibirsk region in 2005 and 2016, we applied methodological techniques for measuring and visualising geographical and structural-technological proximity (STB) of a region in relation to other constituent entities of the Russian Federation. The Novosibirsk region is located in the middle of the country and has a diversified structure of economic activities and science. For this particular region, there has been an increase in the likelihood of the emergence of knowledge spillover channels with various European regions of Russia and some regions of the Urals and the Far East. Proximity matrices can be used in econometric studies to test hypotheses about the impact of different forms of proximity on regional economic growth. Recommendations to enhance knowledge spillover coincide with the proposals to support the areas of innovative development stated in The Strategy of Spatial Development of the Russian Federation for the period until 2025.

Chukchi-Speaking Communities in Three Russian Regions

Sibirica ◽  
2019 ◽  
Vol 18 (2) ◽  
pp. 78-124
Author(s):  
Maria Pupynina ◽  
Yuri Koryakov
Keyword(s):  
Russian Federation ◽  
Language Shift ◽  
Russian Regions ◽  
Economic Activities ◽  
Local Authorities ◽  
The Russian Federation

The Chukchi-speaking population is distributed within three regions of the Russian Federation—Chukotka, Kamchatka, and Yakutia. Because of the lack of regular transportation between these regions and different attitudes toward the Chukchi from the local authorities, Chukchi-speaking communities in these regions have become isolated from one another and have been developing independently. This article observes the dynamics of language shift in all Chukchi-speaking areas through the analysis of the data of the Russian Censuses (1897–2015), literature sources, and personal observations. The figures in this article illustrate the distribution of Chukchi-speaking communities within their historical and modern homeland, Chukchi vernacular zones, the participation in traditional economic activities, and contacts with other languages.

scholarly journals Decomposition of Regional Development Shifts

2019 ◽  
Vol 9 (2) ◽  
pp. 3552-3557
Keyword(s):  
Regional Development ◽  
Russian Federation ◽  
Socioeconomic Development ◽  
Russian Regions ◽  
Economic Activities ◽  
Regional Effect ◽  
Federal Level ◽  
Industry Effect ◽  
The Russian Federation ◽  
National Industry

No breakthrough in the economic development of the Russian Federation could be achieved without the maximum utilisation of the inner regional potential. This implies high relevance of studies concerning the aspects of influence produced by internal and external factors on regional development, as well as analyses of the existing conditions at the macroeconomic level that support or hinder the engagement of inner regional reserves and opportunities in the regions' socioeconomic development. This would make the basis for a more comprehensive view of the regional system and its inherent properties, helping to identify ways to manage regional development. Objectives. Analysis and decomposition of developmental shifts in the Russian regions and their classification based on internal and external influences. Methods. The primary research method is the shift-share analysis method. The methods of logical and statistical analysis, particularly, correlation analysis, are also used. Results. The driver effects of shifts are calculated at the national, industry, and regional levels for 80 regions of the Russian Federation and the period comprising two time points, 2012 and 2017. The regional and industry effects are analysed by the types of economic activities. It is established that, firstly, the regional effect is negative for most regions and, secondly, the industry effect (in combination with the national effect) acts to smooth out the negative regional effect. Conclusions. A conclusion is made that positive shifts can be achieved both in strong and weak regional economies. Generally, the shifts in Russian regions are mostly influenced specifically by the internal regional conditions, which are mostly adverse, suggesting high importance of regional effects. The research highlights the significance of industry policies at the federal level, primarily in economic activities such as agriculture and manufacturing, and the need for improvement of regional policies implemented at the federal level to raise the number of self-developing regions.

DIGITALIZATION OF ECONOMIC ACTIVITY: RISKS AND THREATS OF THE NEW ERA

2021 ◽  
pp. 133-145
Author(s):  
Evgeniy A. Voronin ◽  
◽  
Igor V. Yushin ◽  
Keyword(s):  
Russian Federation ◽  
Economic Activity ◽  
Information Society ◽  
Information Technologies ◽  
Economic Security ◽  
Digital Economy ◽  
Economic Activities ◽  
New Era ◽  
National Economic ◽  
The Russian Federation

This article discusses the current issues of the development of the digital economy. The significant role of information technologies in the development of modern production and services is noted. The development of digital means of economic activity creates new risks that are not yet sufficiently taken into account by modern economic mechanisms. The digitalization of economic activity is the basis for the emergence of new types of economic activity, as well as a fundamental change in traditional ones. The Digital Economy of the Russian Federation program is a set of measures in various fields of activity aimed at stimulating the creation of an information society. According to the" Strategy for the Development of the information Society in the Russian Federation for 2017-2030", a distinctive feature of the information society is the critical level of influence of information on the economic, socio-cultural living conditions of citizens. Such a definition takes into account the possibility of applying certain information in economic activities. Consideration of such changes should be reflected in the Information Security Document, the updating of which is an actual issue of national economic security.

scholarly journals Global Trend of Regional Policy Greening as a Factor of Social and Economic Growth of Regions in the Russian Federation

2021 ◽  
Vol 92 ◽  
pp. 07052
Author(s):  
Anna Popova ◽  
Marina Rudenko
Keyword(s):  
Economic Growth ◽  
Sustainable Development ◽  
Russian Federation ◽  
Regional Policy ◽  
Value Added ◽  
Modern World ◽  
Regional Environment ◽  
Policy Structure ◽  
Perm Krai ◽  
The Russian Federation

Research background: Sustainable development, social and economic growth not damaging the natural environment are one of the most acute problems in the modern world. The issues of the regional sustainable development in the Russian Federation as the purpose of regional policy and aspects of correlation between socio-economic development and state of regional environment were discussed in scientific papers of D.V. Novachenko, D.V. Malova, O.K. Tsapieva, L.V. Shchukina, E.A. Khrabrova, O.V. Vilchinskoy, Yu.G. Neudakhina, A.V., Okuneva, Boronnikov, D.V., E.A. Guseva, D.A., N.N. Yashalova, N.L. Yatsukova, A. Yu. Davankova, L.K., Kazantseva, T.O. Tagaeva, M.F. Zamyatina, P.V. Druzhinin, G.T. Shkiperova, O.V. Potasheva, A.A. Bashirova and others. Purpose of the article: The purpose of this article is to develop measures to improve socio-economic growth in regions on the base of theoretical and methodological substantiation of greening regional policy. Methods: Systematic approach, methods of analysis and synthesis, logical and econometric modelling were used in this research. Findings & Value added: The necessity of including the environmental component in the regional policy structure was approved; the process of regional policy greening was determined; the author’s methodical approach to evaluate the performance of regional policy greening was elaborated; positive changes in social and economic growth were identified with the intensification of regional policy greening; by the example of Perm Krai measures to promote the regional policy greening performance were developed.

Influence analysis of production factors on the economic growth of the regions

2020 ◽  
Vol 92 (3) ◽  
pp. 107-119
Author(s):  
A. A. Pakhomov ◽  
Keyword(s):  
Economic Growth ◽  
Russian Federation ◽  
Value Added ◽  
Production Method ◽  
Gross Regional Product ◽  
Educational Organizations ◽  
Production Factors ◽  
The Russian Federation ◽  
Regional Product

The article sets out a methodology for analysis of the influence of production factors of a certain territory, in this case, the territory of a subject of the Russian Federation, on the dynamics of the gross regional product (GRP) for 2002–2018. The GRP, calculated by the production method as the region’s gross value added at current prices, is the region’s most methodically unaffected indicator. The scientific novelty is the use in the work of indicators, in the author’s opinion, which completely characterize production factors, and the determination of the power of influence of these factors on the dynamics of GRP. The results obtained and the developed database can be used by the regional and municipal authorities, scientific and educational organizations.

scholarly journals Development of a Methodological Approach to Medium-Term Forecasting of the Regional Economic Growth Based on the Decomposition of Macro-Forecast Indicators for Russia

2020 ◽  
pp. 63-74
Author(s):  
Andrey Polynev
Keyword(s):  
Economic Growth ◽  
Growth Rate ◽  
Russian Federation ◽  
Growth Rates ◽  
Economic Activity ◽  
Methodological Approach ◽  
Regional Economic Growth ◽  
Medium Term ◽  
Federal Districts ◽  
The Russian Federation

The article presents a methodological approach to the development of a medium-term forecast of GRP growth rates in regions (subjects of the Russian Federation and Federal districts) in the context of the main types of economic activity based on the decomposition of macroeconomic forecast indicators for Russia. The key factors that have a significant impact on the dynamics of the current regional economic growth, including macroeconomic, territorial and external ones, should be taken into account in forecasts of regional development. The author mentions examples of domestic practices of scientific research in the field of forecasting in the regions of Russia according to the main macroeconomic indicators, including GRP. The paper states the methodological basis and fundamental principles of forecasting of regional indicators of the economic growth according to the main types of economic activity. As a key factor an indicator determining the dynamics of production in the sectors of regional economy, the growth rate of investments into fixed capital is used which is determined by the presence of a functional relationship between these characteristics on the basis of the multiplier ratio. On the basis of the developed methodological approach, the author estimates the growth rate of GRP of Russian regions according to the main types of economic activity for the period until 2024. The paper presents the results of the GRP forecast for Federal districts, as well as the share of GRP investments in them. The article shows the regions of the Russian Federation with the highest GRP growth rates in the medium term and trends of changes in the levels of interregional differentiation in investment and economic activity in Russia from 2000 to 2017 and for the forecasted period until 2024.

scholarly journals Development of high-tech production and growth of non-resource exports in the context of increasing threats to Russia's national economic security

2020 ◽  
Vol 8 (1) ◽  
pp. 136-140
Author(s):  
Aleksey Rodionov
Keyword(s):  
Russian Federation ◽  
Oil And Gas ◽  
Raw Materials ◽  
Economic Security ◽  
High Tech ◽  
Economic Activities ◽  
Fixed Assets ◽  
National Economic ◽  
Macroeconomic Indicators ◽  
The Russian Federation

Article presents the results of analysis of the most significant threats to Russia's economic security that materialized in late 2019 – early 2020. The problems of significant dependence of Russia's key macroeconomic indicators on the parameters of oil and gas exports are Identified. The priorities of increasing non-resource exports, as well as increasing the volume of high-tech closed-loop production are outlined. Indicators of investments aimed at reconstruction and modernization in the total volume of investments in fixed assets for high-tech economic activities in the Russian Federation are analyzed. Indicators of investments aimed at reconstruction and modernization in the total volume of investments in fixed assets by types of economic activity in the raw materials sector of the Russian Federation are analyzed.

THE BASIC DIRECTIONS OF DIRECT FOREIGN INVESTMENTS ATTRACTION INTO THE RUSSIAN REGIONS

2019 ◽  
pp. 31-41
Author(s):  
L.M. Kuznetsova
Keyword(s):  
Economic Growth ◽  
Russian Federation ◽  
Import Substitution ◽  
Russian Regions ◽  
Foreign Investments ◽  
The Russian Federation ◽  
Foreign Assets

The urgency of the theme proceeds from the necessity to finance economic growth of the economy of the Russian Federation. In the article government mechanisms and basic directions of direct foreign investments attraction into Russian regions are considered. Advantages of direct for-eign investments attraction to Russia are defined, and new import substitution strategy is suggested which will be aimed at acquisition of foreign assets and production under the contract abroad.

Studying the innovative development of regional economy as an imperative of sustainable socio-economic growth in Russia, using neural network modeling

2021 ◽  
Vol 20 (8) ◽  
pp. 1394-1414
Author(s):  
Nikolai P. LYUBUSHIN ◽  
Elena N. LETYAGINA ◽  
Valentina I. PEROVA
Keyword(s):  
Neural Network ◽  
Economic Growth ◽  
Neural Networks ◽  
Russian Federation ◽  
Network Modeling ◽  
Innovation Activity ◽  
Neural Network Modeling ◽  
Innovative Development ◽  
Russian Regions ◽  
The Russian Federation

Subject. The article deals with the innovative potential of Russian regions in light of the national goal of the Russian Federation development, reflecting decent and productive work. Objectives. The purpose is to study the innovation activity in Russian regions, using neural networks, to ensure breakthrough innovative development of the Russian economy. Methods. We employ a cluster analysis on the basis of neural network modeling, using information technologies. For the research, we selected neural networks (Kohonen self-organizing maps), which are focused on unsupervised learning and are a promising tool for clustering and visualization of multidimensional statistical data. Results. The result of neural network modeling was the ranking of 85 regions of the Russian Federation into 5 compact groups (clusters) regardless of their affiliation to federal districts of the Russian Federation. The study shows that there is a strong differentiation of the number of regions in these clusters. We obtained average values of indicators in the clusters and compared them with all-Russian indicators. Conclusions. Breakthrough in the socio-economic growth of the Russian Federation is associated with a set of measures that involve stimulating innovation activities in regions, which are characterized by different level of innovation development. Such measures will increase the interest of the real sector of the economy in using scientific development, advanced production technologies, higher-productivity employment opportunities, and, as a result, will encourage socio-economic growth and people's quality of life.

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