Forecasting of Socio-Economic Development of the Russian Regions
The regional differentiation makes impossible the sustainable socio-economic development of the subjects of the Russian Federation without the monitoring public governance results in space and time. Despite the comprehensive approach of the current procedure, approved by the federal government, it...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Russian Academy of Sciences, Institute of Economics of the Ural Branch
2017-12-01
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| Series: | Экономика региона |
| Subjects: | |
| Online Access: | http://www.economyofregion.com/archive/2017/67/2985/pdf/ |
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| author | Galina Yuryevna Gagarina Evgeny Ivanovich Dzyuba Roman Vladimirovich Gubarev Fanil Saitovich Fayzullin |
| author_facet | Galina Yuryevna Gagarina Evgeny Ivanovich Dzyuba Roman Vladimirovich Gubarev Fanil Saitovich Fayzullin |
| author_sort | Galina Yuryevna Gagarina |
| collection | DOAJ |
| description | The regional differentiation makes impossible the sustainable socio-economic development of the subjects of the Russian
Federation without the monitoring public governance results in space and time. Despite the comprehensive approach of the
current procedure, approved by the federal government, it does not adequately assess the executive authorities effectiveness.
Its main problem is the impossibility to assume such important administrative function as forecasting the social and economic
development of Russian territorial subjects. The authors propose an alternative methodology on the basis of the system economic
theory. This technique is implemented in several consecutive stages. Firstly, we develop the system of 30 indicators. Secondly, we
normalize the values of the indicators using the method of pattern. Thirdly, we calculate the index of the social and economic
development of Russian regions for 2011–2015 assuming that the indicators are equal. Last, we group Russian regions into
clusters according to the level of their social and economic development using neural network technologies (Kohonen selforganizing
maps). Only 9 in 80 subjects of the Russian Federation (RF) had the degree of realizing the social and economic
potential higher than 40 % during the period under consideration. In 2011–2015, the most of regions had a low and lower
than average level of social and economic development (with an aggregate share about 64.3 %). It means that, under current
conditions, the majority of the RF regions have considerable reserves for realizing their social-economic potential. In particular,
the absence of the territorial subjects with a high level of social and economic development proves that. The authors have
simulated the social and economic situation of the RF subjects by means of an adequate Bayesian neural networks. The obtained
results can be used as the basis for further research in the field of evaluating executive authorities effectiveness and forecasting
the level of social and economic development of Russian regions. |
| first_indexed | 2024-03-12T08:56:48Z |
| format | Article |
| id | doaj.art-6977489e297245ed9d31871b1acbc003 |
| institution | Directory Open Access Journal |
| issn | 2072-6414 2411-1406 |
| language | English |
| last_indexed | 2024-03-12T08:56:48Z |
| publishDate | 2017-12-01 |
| publisher | Russian Academy of Sciences, Institute of Economics of the Ural Branch |
| record_format | Article |
| series | Экономика региона |
| spelling | doaj.art-6977489e297245ed9d31871b1acbc0032023-09-02T15:55:07ZengRussian Academy of Sciences, Institute of Economics of the Ural BranchЭкономика региона2072-64142411-14062017-12-011341080109410.17059/2017-4-9Forecasting of Socio-Economic Development of the Russian RegionsGalina Yuryevna Gagarina0Evgeny Ivanovich Dzyuba 1Roman Vladimirovich Gubarev2Fanil Saitovich Fayzullin3 Plekhanov Russian University of EconomicsBranch of All-Russia Popular Front of the Republic of Bashkortostan Plekhanov Russian University of EconomicsInstitute of Social and Economic Research of the Ufa Scientific Centre of RASThe regional differentiation makes impossible the sustainable socio-economic development of the subjects of the Russian Federation without the monitoring public governance results in space and time. Despite the comprehensive approach of the current procedure, approved by the federal government, it does not adequately assess the executive authorities effectiveness. Its main problem is the impossibility to assume such important administrative function as forecasting the social and economic development of Russian territorial subjects. The authors propose an alternative methodology on the basis of the system economic theory. This technique is implemented in several consecutive stages. Firstly, we develop the system of 30 indicators. Secondly, we normalize the values of the indicators using the method of pattern. Thirdly, we calculate the index of the social and economic development of Russian regions for 2011–2015 assuming that the indicators are equal. Last, we group Russian regions into clusters according to the level of their social and economic development using neural network technologies (Kohonen selforganizing maps). Only 9 in 80 subjects of the Russian Federation (RF) had the degree of realizing the social and economic potential higher than 40 % during the period under consideration. In 2011–2015, the most of regions had a low and lower than average level of social and economic development (with an aggregate share about 64.3 %). It means that, under current conditions, the majority of the RF regions have considerable reserves for realizing their social-economic potential. In particular, the absence of the territorial subjects with a high level of social and economic development proves that. The authors have simulated the social and economic situation of the RF subjects by means of an adequate Bayesian neural networks. The obtained results can be used as the basis for further research in the field of evaluating executive authorities effectiveness and forecasting the level of social and economic development of Russian regions.http://www.economyofregion.com/archive/2017/67/2985/pdf/efficiency of public administrationevaluation methodologyspatial developmentinterregional differentiationregional socio-economic developmentsystemic approachclustering of regionsneuromodulationmultilayer perceptronBayesian neural networks |
| spellingShingle | Galina Yuryevna Gagarina Evgeny Ivanovich Dzyuba Roman Vladimirovich Gubarev Fanil Saitovich Fayzullin Forecasting of Socio-Economic Development of the Russian Regions Экономика региона efficiency of public administration evaluation methodology spatial development interregional differentiation regional socio-economic development systemic approach clustering of regions neuromodulation multilayer perceptron Bayesian neural networks |
| title | Forecasting of Socio-Economic Development of the Russian Regions |
| title_full | Forecasting of Socio-Economic Development of the Russian Regions |
| title_fullStr | Forecasting of Socio-Economic Development of the Russian Regions |
| title_full_unstemmed | Forecasting of Socio-Economic Development of the Russian Regions |
| title_short | Forecasting of Socio-Economic Development of the Russian Regions |
| title_sort | forecasting of socio economic development of the russian regions |
| topic | efficiency of public administration evaluation methodology spatial development interregional differentiation regional socio-economic development systemic approach clustering of regions neuromodulation multilayer perceptron Bayesian neural networks |
| url | http://www.economyofregion.com/archive/2017/67/2985/pdf/ |
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