Impact of regulatory framework rigidity on poverty in the regions of Russia

2020 ◽  
pp. 62-79
Author(s):  
P. N. Pavlov
Keyword(s):  
Economic Activity ◽  
Regional Level ◽  
Institutional Factors ◽  
Federal Regulations ◽  
Russian Regions ◽  
Poverty Dynamics ◽  
Regulatory Burden ◽  
Sectoral Structure ◽  
The Impact ◽  
Regions Of Russia

The paper analyzes the impact of the federal regulatory burden on poverty dynamics in Russia. The paper provides regional level indices of the federal regulatory burden on the economy in 2008—2018 which take into account sectoral structure of regions’ output and the level of regulatory rigidity of federal regulations governing certain types of economic activity. Estimates of empirical specifications of poverty theoretical model with the inclusion of macroeconomic and institutional factors shows that limiting the scope of the rulemaking activity of government bodies and weakening of new regulations rigidity contributes to a statistically significant reduction in the level of poverty in Russian regions. Cancellation of 10% of accumulated federal level requirements through the “regulatory guillotine” administrative reform may take out of poverty about 1.1—1.4 million people.

Revealing of the specificity of mortgage housing lending based on the results of clustering of regions

2021 ◽  
Vol 27 (12) ◽  
pp. 2679-2697
Author(s):  
Lyudmila E. ROMANOVA ◽  
Anna L. SABININA ◽  
Andrei I. CHUKANOV ◽  
Dar’ya M. KORSHUNOVA
Keyword(s):  
Systems Approach ◽  
Mortgage Lending ◽  
Effective Algorithm ◽  
Russian Regions ◽  
Local Conditions ◽  
Partitioning Around Medoids ◽  
Analysis And Synthesis ◽  
The Russian Federation ◽  
The Impact ◽  
Regions Of Russia

Subject. This article deals with the particularities of the development of housing mortgage lending in the regions of Russia. Objectives. The article aims to substantiate the need for clustering of territorial entities by level of development of mortgage housing lending in Russia and test the most effective algorithm for mortgage clustering of regions. Methods. For the study, we used a systems approach, including scientific abstraction, analysis and synthesis, and statistical methods of data analysis. The algorithm k-medoids – Partitioning Around Medoids (PAM) was also used. Results. Based on the results of the study of regional statistics of the Russian Federation, the article reveals a significant asymmetry in the values of key socioeconomic indices that determine the level and dynamics of housing mortgages in the regions. This necessitates the clustering of territorial entities according to the level of development of mortgage housing lending in the country. To take into account the impact of various local conditions in assessing the prospects for the development of regional housing mortgages, the article proposes an indicator, namely, the integral regional mortgage affordability index. On its basis, in accordance with the selected clustering procedure, the article identifies five mortgage clusters in Russia and identifies their representative regions. Conclusions. Based on the analysis of the specificity of the development of regional mortgages in the Tula Oblast, taking into account the implementation of the target State programme, the article concludes that it is necessary to improve the mechanisms for financing regional mortgage programmes and justifies the need to develop differentiated programmes for the development of housing mortgages in groups of Russian regions.

scholarly journals Macroeconomic Relationships for Russian Economic Regions

2019 ◽  
Vol 71 ◽  
pp. 02001
Author(s):  
A.N. Bereznyatskiy ◽  
B.E. Brodsky
Keyword(s):  
Russian Federation ◽  
Economic Activity ◽  
Regional Level ◽  
Russian Regions ◽  
Economic Region ◽  
The Russian Federation ◽  
Main Item ◽  
Economic Regions

This paper deals with macroeconomic relationships for Russian economic regions. An economic region is the main item of the regional statistics of the Russian Federation. Nowadays there are near 90 of regions and according to classification these can be industrial, agro- or subsidized regions A study is based upon the disaggregated macromodel for the Russian economic region. Then classification of the Russian regions by types of economic activity is made. Finally, we construct macroeconomic relationships for Russian economic regions specific by their type of economic activity This paper can be considered as the first attempt to create the model of the Russian regional level.

Assessing the impact of banking intermediationon the economy of Russian regions: The post-crisis trends

2017 ◽  
pp. 103-122 ◽  
Author(s):  
K. Krinichansky ◽  
A. Fatkin
Keyword(s):  
Positive Relationship ◽  
Composite Indicator ◽  
Regional Level ◽  
Russian Regions ◽  
Banking Services ◽  
Significant Positive Relationship ◽  
Per Capita ◽  
Relationship Of ◽  
The Impact ◽  
The Relationship

The paper explores the changes in relative levels of banking services availability in Russia’s regions in 2007-2015 and the relationship between the regional financial development characteristics and the indicators of GRP and investments on the regional level in 2002-2014. For 2013-2015, the paper demonstrates the divergence of regions by the composite indicator - the composite banking services density index by region and its separate components. A significant positive relationship of indicators characterizing the regions’ financial mediator services density with the indicators of GRP has been revealed. This relationship is non-linear which is demonstrated in different sensitivity of GRP per capita by groups of regions to the indicators of financial mediation, so that regions with relatively lower or, on the contrary, higher GRP per capita show weaker or no relationship between finance and growth, whereas regions of “central” groups with medium values of GRP demonstrate stronger connection.

scholarly journals Econometric Modelling of the Impact of Knowledge Diffusion and Other Factors on Exports of Russian Regions

2020 ◽  
Vol 17 (4) ◽  
pp. 811-819
Author(s):  
O. S. Mariev ◽  
◽  
N. S. Teplyakov ◽  
Keyword(s):  
Positive Impact ◽  
Knowledge Diffusion ◽  
Russian Regions ◽  
Design Strategies ◽  
Economic Sectors ◽  
Main Hypothesis ◽  
Sectoral Structure ◽  
Research Findings ◽  
The Impact ◽  
The Relationship

This study focuses on the sectoral structure of exports of Russian regions and its dynamics. We also explore the reasons for similarities in export portfolios of regions. Despite the differences in geography, climate and capital availability, Russian regions have more similarities than differences in terms of their export baskets. This conclusion is valid for the six economic sectors we examined based on observations from 1998 to 2018. This paper aims to clarify the nature of the relationship between the structure of exports and knowledge diffusion. Our main hypothesis is that knowledge diffusion has a positive impact on the similarity of exports in Russian regions. Using econometric tools, we bring to light the following patterns: first, knowledge diffusion has a positive effect on similarity of regional exports; second, an increase in the distance between Russian regions leads to a decrease in the similarity of their export baskets, while the presence of a common border leads to the opposite; and finally, a growing difference in socio-economic indicators leads to a decrease in the similarity of regions’ export baskets. The research findings could be used to design strategies for development of regional exports.

Does public sector crowd out entrepreneurship? Evidence from the EU regions

2018 ◽  
Vol 24 (4) ◽  
pp. 866-881 ◽  
Author(s):  
Eva Zikou ◽  
Nikos Varsakelis ◽  
Aikaterini K. Sarri
Keyword(s):  
Public Sector ◽  
Economic Activity ◽  
Value Added ◽  
Regional Level ◽  
Regional Economic ◽  
Content Type ◽  
The Public ◽  
Entrepreneurial Activities ◽  
The Impact

Purpose The decision to engage in entrepreneurial activities is grounded in personal characteristics (motivation) and external environmental factors. One of the main external factors might be the structure of the regional economic activity. Does a high share of the public sector affect positively regional entrepreneurship or vice versa? Does the diversity in regional economic activity is conducive for entrepreneurial development or the regional comparative advantage as expressed by spatial economies of scale offering more entrepreneurial opportunities? Even though economic analysis has extensively examined the impact of the public sector size on the overall national economic activity (the crowding out effect), this impact has not been into scrutiny at regional level on microeconomic issues, such as the decision to engage in entrepreneurial activities. The authors further investigate the relation between diversity and entrepreneurship at regional level. The paper aims to discuss these issues. Design/methodology/approach This paper uses data for 264 NUTS II EU regions. The time span of the data set is 1999-2008. The paper applies panel data analysis to explain the cross-time cross-section variation of the dependent variable: the self-employment share in total employment at regional level. In order to measure the existence of crowding out from public sector to regional entrepreneurship, the authors use the share of regional public sector gross value added over total regional gross value added. The diversity of the regional economic activity is measured by the Herfindahl-Hirschman Concentration Index across sectors. Findings The findings of the paper show that there is a negative correlation between public sector share and regional entrepreneurship. Hence, as at national level, the increase in the role of the public sector in the regional economic system crowds out regional entrepreneurship. The second finding indicates that the impact of the diversity of the regional economic activity on regional entrepreneurship is inconclusive. Originality/value The originality of this paper is due to the fact that the role of the public sector on regional economic phenomena, such as entrepreneurship, is examined for the first time. Also, the investigation of the relationship between diversity (vs localization economies) and entrepreneurship is performed using data for the full sample of regions of the European Union. The findings of the paper have significant policy implications since they provide useful inputs for the design of the regional development policy. The reduction of the public sector at regional level may contribute in entrepreneurial development and finally in regional economic growth and prosperity. Besides, the regional industrial policy should focus on the exploitation of the spatially constraint economies of scope in the framework of the Triple Helix model.

scholarly journals Neural network modeling of tourism development as a factor of sustainable economic growth in Russian regions

2021 ◽  
Vol 291 ◽  
pp. 02023
Author(s):  
Elena Letiagina ◽  
Valentina Perova ◽  
Aleksander Gutko ◽  
Aleksander Kutasin
Keyword(s):  
Neural Network ◽  
Russian Federation ◽  
Economic Activity ◽  
Dimensional Space ◽  
Network Modeling ◽  
Neural Network Modeling ◽  
Russian Regions ◽  
Tourism Sector ◽  
The Russian Federation ◽  
Regions Of Russia

The features of the development of the tourism sector in the regions of the Russian Federation, which have an impact on the socio-economic development of the country, have been investigated. Analysis of the current state of the tourism sector, classified as the main types of economic activity, is relevant and important for increasing the competitiveness of the regions of the Russian Federation and ensuring the economic security of the state. The study is aimed to model and analyze tourist cluster formations in Russia. The study of tourist activity in the regions of Russia based on the indicators of the database of the Federal State Statistics Service was carried out using a new promising approach - cluster analysis using the scientific and methodological apparatus of artificial neural networks. The distribution of Russian regions into five tourist clusters has been obtained as a result of clustering multidimensional data using neural networks - self-organizing Kohonen maps, which are focused on self-study, and modern information technologies. In neural network modeling, the six-dimensional space of tourism development indicators was mapped, taking into account the topology, into a two-dimensional space, which made it possible to visualize the results of grouping regions by tourist clusters. The features of the development of the tourism sector in the regions of the Russian Federation have been revealed by the totality of the considered indicators The obtained results state that there is a strong variation in the number of regions by tourist clusters and the ametric nature of the development of tourist activity in the regions of Russia. The results of the study are of practical significance for the strategic planning of the tourism sector development, which ensures the development of domestic and inbound tourism. Analysis of the functioning of the tourism sector in the regions of the Russian Federation allows concluding the necessity to take a set of measures to stimulate effective investment activity in a number of tourism clusters, harmonizing the strategies of the state and business, which will contribute to the renewal and competitiveness of this type of economic activity.

scholarly journals Economic and statistical analysis of russian regions' environmental and economic activity localization

2021 ◽  
Vol 2 (11) ◽  
pp. 87-99
Author(s):  
Yury I. Treshhevskij ◽  
◽  
Anna Y. Kosobuczkaya ◽  
Lev K. Garin ◽  
◽  
...  
Keyword(s):  
Economic Activity ◽  
Socioeconomic Development ◽  
Russian Regions ◽  
Low Carbon ◽  
Ecological Situation ◽  
Economic Sectors ◽  
Virtual Groups ◽  
Global Environmental Problems ◽  
Geometric Space ◽  
The Impact

Currently, many scientists and economists write about the seriousness of global environmental problems, paying great attention to the interdependence of ecology and economic development. The ecological situation in the regions of Russia directly depends on the impact of economic sectors on the environment. At the same time, the important features of a sustainable economy are the efficient use of natural resources, reduction of environmental pollution, low carbon emissions, etc. The study of the ecological situation requires constant updating of materials, the identification of new patterns of development. This study is a comprehensive analysis of the localization of the ecological and economic activity of Russian regions. In the process of processing the materials, official statistical data on the state of the social, economic and ecological subsystems of the regions were used. The results of the analysis made it possible to identify a number of patterns in the distribution of Russian regions, taking into account the localization of environmental and economic activity. To form virtual groups of regions, homogeneous in terms of the totality of indicators characterizing the ecological and economic activity of Russian regions, we used cluster analysis, which is a research method that allows for a multidimensional grouping of objects. As a result, observations are depicted by groups of points in geometric space, called clusters. By analyzing the dendrogram, the regions of the country are divided into a certain number of clusters. Since clustering by the K-means method does not automatically rank clusters, they are sorted by the sum of normalized indicators, and the higher the value of the sum of these indicators, the more unbalanced the cluster is. The use of this method has been widely reflected in the study of the problems of socioeconomic development of regions.

scholarly journals The First and Second Waves of the COVID‑19 Pandemic in the Russian Regions: Comparison of the Change in the Mortality Rate

2001 ◽  
Vol 14 (7) ◽  
pp. 1028-1038
Author(s):  
Pavel V. Druzhinin ◽  
◽  
Ekaterina V. Molchanova
Keyword(s):  
Mortality Rate ◽  
Internet Resource ◽  
Russian Regions ◽  
Global Challenge ◽  
Leading Role ◽  
Russian Economy ◽  
Geographical Factors ◽  
Significant Damage ◽  
The Impact ◽  
Regions Of Russia

The emergence of the COVID‑19 pandemic has become a new global challenge for the whole humankind affecting all spheres of society. The purpose of this article is to identify the complex effect of various factors on the mortality rate in Russian regions during the first and second waves of the coronavirus pandemic. As the information base of the study, official statistical publications («Regions of Russia», «Natural Population Movement») were used, as well as data from the official Internet resource on the situation with the incidence of COVID‑19 in the regions of Russia. With the help of economic and mathematical tools, the impact of demographic, socio-economic, environmental, medical and geographical factors on the mortality rate in Russian regions was assessed. The calculations allowed to establish the causes of a significant increase in mortality in the Russian regions, as well as to identify significant differences between the first and second waves of the pandemic. The study showed that demographic and geographical factors played the leading role, but their influence at different time periods had its own characteristics. The coronavirus pandemic accelerated the process of reducing the country’s population, and also caused significant damage to the Russian economy. The results of the study can be used in the field of medico-demographic policy aimed at preserving the social (population) health of the nation

scholarly journals Problems and Prospects of the Implementation of «Garbage» Reform in Russian Regions

2020 ◽  
pp. 51-55
Author(s):  
Oleg Sergeyevich Poroshin ◽  
Alexander Borisovich Khramtsov
Keyword(s):  
Waste Management ◽  
Garbage Collection ◽  
Regional Level ◽  
Municipal Waste ◽  
Practical Significance ◽  
Russian Regions ◽  
Internet Resources ◽  
Solid Municipal Waste ◽  
On Line ◽  
Regions Of Russia

This paper dwells upon the garbage reform, the problems of its implementation in the regions of Russia. The relevance and practical significance are connected with increasing environmental require-ments for the life of modern man and the need to analyze the implementation of the reform in the country. As a result of the reform, the authority for handling solid municipal waste (SMW) was trans-ferred to the regional level through the creation of regional operators; garbage collection and sorting are defined as a separate utility service; the scheme of waste management and the payment scheme for their removal and sorting have been changed. The assessment of the current situation in the regions made it possible to formulate key problems that are all-Russian in nature: the lack of containers for gar-bage sorting, collisions in regulations, the non-compliance of landfills with modern requirements, unauthorized landfills, the reluctance of people to sort garbage and others. A number of recommenda-tions were proposed, in particular, training the population in separate garbage collection, including on-line Internet resources.

scholarly journals Analysis of pasture areas in Brazil using official data and time series of vegetation index

2018 ◽  
Author(s):  
David Oliveira Ramin ◽  
Gleyce Kelly Dantas Araujo Figueiredo
Keyword(s):  
Land Use ◽  
Economic Activity ◽  
Satellite Images ◽  
Vegetation Index ◽  
Temporal Dynamics ◽  
Regional Level ◽  
Land Use Classification ◽  
The Impact ◽  
Official Data ◽  
Over Time

The temporal dynamics of pasture areas is strongly associated with the change in economic activity in the area. The impact of this transition, impacts the environmental, economic and social parameters. The evaluation of the temporal dynamics of pasture areas is extremely important for the generation of information to support decisions whether at the local or regional level, public or private. The use of satellite images and geographic information systems is completely indispensable for the evaluation of the dynamics of pasture areas over time, and this is the fact that motivates this research to identify areas of pasture in different years from official maps of land use classification and to evaluate, by NDVI series, which is associated strongly to the biomass of vegetation, the areas of retraction or increase of pasturelan areas, thus identifying the dynamics of land use transition.

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