Determining the conditions for sustainable development of the Russian economy

2020 ◽  
Vol 19 (11) ◽  
pp. 2093-2115
Author(s):  
V.V. Smirnov
Keyword(s):  
Neural Network ◽  
Cluster Analysis ◽  
Sustainable Development ◽  
Systems Approach ◽  
Political Stability ◽  
Russian Economy ◽  
Globalizing World ◽  
The Neural Network ◽  
Development Goals ◽  
And Cluster Analysis

Subject. The article addresses conditions for sustainable development of the Russian economy. Objectives. The purpose is to link the limit of sustainability of the Russian economy with required conditions. Methods. The study draws on the systems approach, using the methods of statistical, neural network, and cluster analysis. Results. I describe scientific ideas about sustainable development of economy, which have been developed in theoretical and practical activities. The World Bank data on environment, social affairs and governance on 17 key sustainable development topics, covering environmental, social and management categories, are used to determine conditions for sustainability of the Russian economy. The neural network analysis of the importance of indicators’ rate of increment shows a hierarchy of priorities. The cluster analysis of indicators’ rate of increment identifies significant clusters. The analysis of key priorities of sustainable development of the Russian economy enables to reveal significant deviations in political stability and in access to electricity. Conclusions. Conditions for sustainable development of the Russian economy are determined by their proximity to the United Nations Sustainable Development Goals. Identifying these conditions in the globalizing world creates an understanding of the real limit and opportunities of the country's development.

Analyzing the "Strategy of Socio-Economic Development of the Chuvash Republic until 2035" content

2021 ◽  
Vol 20 (2) ◽  
pp. 299-324
Author(s):  
Valerii V. SMIRNOV
Keyword(s):  
Neural Network ◽  
Cluster Analysis ◽  
Economic Development ◽  
Growth Rates ◽  
Systems Approach ◽  
Cultural Institutions ◽  
Socio Economic Development ◽  
Chuvash Republic ◽  
Number Of Visits ◽  
And Cluster Analysis

Subject. The article addresses a strategy for socio-economic development of the region. Objectives. The purpose is to define contradictions and opportunities to achieve the expected results of the "Strategy of Socio-economic Development of the Chuvash Republic until 2035". Methods. The study rests on the systems approach, using the methods of statistical, neural network, and cluster analysis. Results. The statistical analysis of trends in expected outcomes of the Strategy implementation enabled to build a median hierarchy of their growth rates, where the indicator of an increase in the number of visits to cultural institutions is a priority in setting the goals for the region’s development. The neural network analysis demonstrates the importance of the growth rate of real accrued wages of employees of organizations and the insignificant value of the increase in the number of visits to cultural institutions for effective achievement of all objectives of the Strategy. The cluster analysis shows the importance of growth rates of indicators of the proportion of organizations engaged in technological innovations, and the proportion of shipped innovative products. The analysis of growth rates of GRP and expenditures of the consolidated budget of the Chuvash Republic reveals a decrease in the cyclical lag of the first dynamic pattern from the second one. Conclusions. For the Chuvash Republic, a strategic priority is to overcome the GRP growth limit through the innovative development of backbone areas of economic activity.

Analyzing the dynamics of administrative indicators in Russia

2021 ◽  
Vol 17 (2) ◽  
pp. 361-384
Author(s):  
Valerii V. SMIRNOV
Keyword(s):  
Neural Network ◽  
Network Analysis ◽  
Systems Approach ◽  
Political Stability ◽  
World Bank Group ◽  
Neural Network Analysis ◽  
Governance Indicators ◽  
The Neural Network ◽  
Bank Group ◽  
General Aspects

Subject. The article discusses the dynamics of the Russian indicators of administration. Objectives. I identify constraints that determine administrative criteria. Methods. The study is based on the systems approach and methods of statistical, cluster and neural network analysis. Results. The article spotlights the stewardship of Russia’s economy today and theoretical considerations on general administrative criterion. I analyzed trends in the Russian administrative indicators, referring to six general aspects of management (Worldwide Governance Indicators, World Bank Group). Using the cluster analysis of growth rates of the Russian administrative indicators, I found major and crucial clusters. Conducting the neural network analysis, I understood the hierarchy of priorities, with the governmental efficiency being the most important one. The supremacy of law, political stability and no violence/terrorism were found to of the least significance. Having evaluated the asymmetry of trends in the Russian administrative indicators against the average, I identified the priority, that us the governmental efficiency, which turns to be a determining criterion of management. Conclusions and Relevance. As a result of the study, I understood what hampers the dynamics of the Russian administrative indicators by determining administrative criteria. I especially point out the possibility of raising the governmental efficiency to maintain the political stability and prevent violence/terrorism by neglecting the supremacy of law, regulatory quality and simulating the anti-corruption activity. The findings contribute to the necessary scope of governmental authorities’ competence to make administrative decisions on the effective stewardship of Russia.

Analyzing the foreign trade competitiveness of the Chuvash Republic

2020 ◽  
Vol 16 (3) ◽  
pp. 478-495
Author(s):  
V.V. Smirnov ◽  
A.M. Mulendeeva
Keyword(s):  
Cluster Analysis ◽  
Foreign Trade ◽  
Systems Approach ◽  
Trade Flow ◽  
Seasonal Fluctuations ◽  
Russian Economy ◽  
Its Regions ◽  
Chuvash Republic ◽  
Trade Competitiveness ◽  
And Cluster Analysis

Subject. The article addresses the foreign trade competitiveness of the region. Objectives. The aims of the study are to investigate the efficiency of international trade of the Chuvash Republic; to conduct aggregated and segmented assessment of foreign trade competitiveness of the Chuvash Republic, and to provide recommendations for improving the trading performance. Methods. The study rests on the systems approach, using the statistical and cluster analysis. Results. We considered the current condition of the Russian economy, highlighted the main problems of its development, and substantiated the possibility of resolving them through increasing the efficiency of foreign trade at the level of the country and its regions. We performed an aggregated and segmented assessment of foreign trade competitiveness of the economy of the Chuvash Republic. It enabled to reveal strengths of importer countries in the general commodity turnover and seasonal fluctuations of exports. Our recommendations for improving foreign trade competitiveness rest on the cluster analysis of significant imports and exports. This analysis unveiled countries that contribute to turnover growth in the Chuvash Republic, as well as the main groups of commodities contributing to the balance of sales volume. Conclusions. To improve the competitiveness of foreign trade of the Chuvash Republic, it is crucial to increase the efficiency of trade flow, i.e. imports from Belarus and the Netherlands, and exports to Armenia and Lithuania.

Analyzing the current effectiveness of the Russian economy's design

2020 ◽  
Vol 8 (8) ◽  
pp. 1476-1496
Author(s):  
V.V. Smirnov
Keyword(s):  
Economic Growth ◽  
Sustainable Development ◽  
Growth Rates ◽  
Systems Approach ◽  
Mineral Resources ◽  
Cash Flows ◽  
Moscow Oblast ◽  
Structural Balance ◽  
Russian Economy ◽  
The Stability

Subject. The article discusses Russia’s economy and analyzes its effectiveness. Objectives. The study attempts to determine to what extent Russia’s economy is effective. Methods. The study is based on the systems approach and the statistical analysis. Results. I discovered significant fluctuations of the structural balance due to changing growth rates of the total gross national debt denominated in the national currency, and the stability of growth rates of governmental revenue. Changes in the RUB exchange rate and an additional growth in GDP are the main stabilizers of the structural balance, as they depend on hydrocarbon export. As a result of the analysis of cash flows, I found that the exports slowed down. Financial resources are strongly centralized, since Moscow and the Moscow Oblast are incrementing their share in the export of mineral resources, oil and refining products and import of electrical machines and equipment. Conclusions and Relevance. The fact that the Russian economy has been effectively organized is proved with the centralization of the economic power and the limits through the cross-regional corporation, such as Moscow and the Moscow Oblast, which is resilient to any regional difficulties ensuring the economic growth and sustainable development. The findings would be valuable for the political and economic community to outline and substantiate actions to keep rates of the economic growth and sustainable development of the Russian economy.

A Russian approach to ensuring economic growth

2021 ◽  
Vol 20 (7) ◽  
pp. 1234-1255
Author(s):  
Valerii V. SMIRNOV
Keyword(s):  
Economic Growth ◽  
Russian Federation ◽  
Systems Approach ◽  
Consumption Expenditures ◽  
Goods And Services ◽  
Russian Economy ◽  
Public Consumption ◽  
The Russian Federation ◽  
The Government ◽  
And Cluster Analysis

Subject. The article investigates a Russian approach to ensuring economic growth. Objectives. The aim is to identify the basis of the Russian approach to ensuring economic growth. Methods. The study rests on the systems approach, using the methods of statistical, neural network, and cluster analysis. Results. The paper defines the structural importance of exports of goods and services, and changes in inventories. It highlights significant links with public consumption expenditures. The Russian approach to ensuring economic growth comes down to devaluation of the national currencyб resulting from the loss of the real inflationary potential of economic growth to maintain the volume of exports of goods and services in the context of maintaining public consumption expenditures. The increase in M2 forces the Central Bank of the Russian Federation to increase its foreign exchange reserves. This has a restraining effect on the growth of Russian Ruble’s monetary exchange rate. This phenomenon causes a drop in the Russian federal loan bond (OFZ) index and a replacement of strategic priorities with tactical ones. Conclusions. The basis of the Russian approach to ensuring economic growth is a reflection of the limits of the Russian economy development and the effectiveness of the Government of the Russian Federation.

Using an artificial neural network for estimating sustainable development goals index

2020 ◽  
Vol 31 (4) ◽  
pp. 1023-1037 ◽  
Author(s):  
Seyed-Hadi Mirghaderi
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Sustainable Development ◽  
Artificial Neural Networks ◽  
Sustainable Development Goals ◽  
Content Type ◽  
The Sustainable Development ◽  
Development Goals ◽  
Artificial Neural

PurposeThis paper aims to develop a simple model for estimating sustainable development goals index using the capabilities of artificial neural networks.Design/methodology/approachSustainable development has three pillars, including social, economic and environmental pillars. Three clusters corresponding to the three pillars were created by extracting sub-indices of three 2018 global reports and performing cluster analysis on the correlation matrix of sub-indices. By setting the sustainable development goals index as the target variable and selecting one indicator from each cluster as input variables, 20 artificial neural networks were run 30 times.FindingsArtificial neural networks with seven nodes in one hidden layer can estimate sustainable development goals index by using just three inputs, including ecosystem vitality, human capital and gross national income per capita. There is an excellent similarity (>95%) between the results of the artificial neural network and the sustainable development goals index.Practical implicationsInstead of calculating 232 indicators for determining the value of sustainable development goals index, it is possible to use only three sub-indices, but missing 5% of precision, by using the proposed artificial neural network model.Originality/valueThe study provides additional information on the estimating of sustainable development and proposes a new simple method for estimating the sustainable development goals index. It just uses three sub-indices, which can be retrieved from three global reports.

scholarly journals Classification–coordination–collaboration: a systems approach for advancing Sustainable Development Goals

2020 ◽  
Vol 7 (5) ◽  
pp. 838-840 ◽  
Author(s):  
Bojie Fu ◽  
Junze Zhang ◽  
Shuai Wang ◽  
Wenwu Zhao
Keyword(s):  
Sustainable Development ◽  
Sustainable Development Goals ◽  
Systems Approach ◽  
Short Term ◽  
Long Run ◽  
Urgent Task ◽  
The World ◽  
Development Goals

Summary It is an urgent task to advance Sustainable Development Goals (SDGs) on different scales in the world. We propose a systems approach to combat this issue, namely `classification–coordination–collaboration'. This approach allows SDGs to realize key breakthroughs over the short-term while achieving sweeping progress over the long run.

scholarly journals Recycling of Communal Waste: Current State and Future Potential for Sustainable Development in the EU

2019 ◽  
Vol 11 (10) ◽  
pp. 2904 ◽  
Author(s):  
Marcela Taušová ◽  
Eva Mihaliková ◽  
Katarína Čulková ◽  
Beáta Stehlíková ◽  
Peter Tauš ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Sustainable Development ◽  
Waste Management ◽  
National Level ◽  
Waste Recycling ◽  
The European Union ◽  
Eu Member States ◽  
Current State ◽  
Waste Production ◽  
And Cluster Analysis

The constant consumption of resources exerts pressure on the environment. In this sense, waste management has obtained increasing attention from the view of a circular economy. The European Union deals with these mentioned aspects, trying maintain long-term competitiveness and to provide sustainable development in accordance with all related environmental aspects. This paper focuses on the evaluation of the production of communal waste in 36 EU countries. The main aim is to evaluate the success of countries’ efforts to decrease waste production and increase recycling rates. The methodology used for the evaluation included data collected from the publicly available database Eurostat, consequent analyses and evaluation in the statistical software JMP 13 through regression, distribution, and cluster analysis, and the interpretation of the results. The results of the cluster analysis showed that despite clear EU waste management legislation, EU member states have significantly different waste management systems at the national level. However, generally, we could see positive correlation between the generation of waste and recycling rates. Although, Malta, Austria, Greece, and Norway recorded a decreasing level of waste recycling over the last several years, some countries (Slovakia, Poland, Czech Republic, Latvia, Lithuania) had significantly lower recycling rates accompanied by low landfill taxes. The evaluation of waste production and recycling can be used for government policy in the area of waste management, as well as for individual communities dealing with communal waste.

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