Modeling the Development of Regional Economy and an Innovation Space Efficiency

Makarov, Valery; Ayvazyan, Sergey; Afanasyev, Mikhail; Bakhtizin, Albert; Nanavyan, Ashkhen

doi:10.17323/1995-459x.2016.3.76.90

Cited by 24 publications

(15 citation statements)

References 4 publications

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“…▪ use of technologies of multiple use of renewable resources in the processing and storage, the transition to non-waste production, the formation and operation of additional plants for processing recycled materials, improving the safety technologies of manufactured products (Makarov, Ayvazyan, Afanasyev, Bakhtizin, & Nanavyan, 2016).…”

Section: 2mentioning

confidence: 99%

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Assessing The Impact Of Resource Potential On The Results Of Agricultural Activity

Kukushina¹,

Okomina²

2019

The European Proceedings of Social and Behavioural Sciences

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Section: 2mentioning

confidence: 99%

“…The fundamental element of these entities is the enterprise. In this connection, the terms are applicable to it as well (Makarov, Ayvazyan, Afanasyev, Bakhtizin, & Nanavyan, 2016).…”

Section: Research Questionsmentioning

confidence: 99%

Assessing The Impact Of Resource Potential On The Results Of Agricultural Activity

Kukushina¹,

Okomina²

2019

The European Proceedings of Social and Behavioural Sciences

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“…В региональных экономических исследованиях актуальным является сравнительный анализ различных сфер жизнедеятельности -социального и экономического развития, экологической и энергетической безопасности [1][2][3][4][5][6][7][8]. Проблематика такого рода исследований обусловлена многовариантностью выбора первичных признаков, расчетных методов и алгоритмов сравнительного анализа.…”

Section: Introductionunclassified

“…Для многомерного сравнительного анализа экономических систем с оцениванием параметра их эффективности, преимущественно используются методы граничного анализа: моделирование граничного производственного потенциала -Stochastic Frontier Analisys [3,11] и непараметрический метод анализа среды функционирования -Data Envelopment Analysis (DEA) [6,[12][13][14][15]. Метод DEA активно применяется в зарубежных исследованиях комплексной энерго-эколого-экономической сравнительной эффективности производственных систем разного уровня, в том числе для межстрановых и межрегиональных сопоставлений [13,14].…”

Section: Introductionunclassified

Differentiation of the economic efficiency in the regions of Russia

Chaika

2020

Statistika i ekonominka

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Purpose. The strategic objectives of sustainable development of the Russian economy include improving energy efficiency and capital efficiency, increasing labor productivity, and reducing the negative impact on the environment. Due to the significant differentiation of the Russian Federation economy, the priorities of these tasks in regions are not the same. There-fore, the analysis of various components of the regional macroeconomic efficiency and the choice of methodical approaches to their composite assessment are being important. The pur-pose of this paper is to test the multidimensional analysis methods of key regional production indicators for measuring the integral indicator – the relative level of economy-wide efficiency of the Russian regions.Materials and methods. “Per unit” indicators of the gross regional product: energy con-sumption, use of fixed assets, labor, and environmental impact, that are calculated by the ROSSTAT data are the basis for assessing of the regional economy efficiency. The research interest of joint consideration of these regional economy indicators is due to their connected-ness as major components of the latent synthetic property of efficiency. The study used meth-ods of comparative multidimensional analysis: nonparametric method of frontier analysis – Data Envelopment Analysis, methods of the average and taxonomic indicator and principal components.Results. The tested methods allowed assessing the differentiation, to rank the regions of the Russian Federation by the level of their economic systems’ efficiency and to identify the “lagging” ones and determine the factors that reduce their positions. The specifics of the ap-plication of the considered methods are noted. Attention is paid to the economic interpreta-tion of the integral indicators. The grouping of regions of the Russian Federation has been car-ried out according to the data of 2016. Twenty-eight regions are classified as “high efficiency” (integral index 0,85–1,0), most of which are effective on all four criteria. The “medium-performing” group (0,75–0,84) comprises thirty-three regions with a reduced level of efficien-cy due to one or two factors: high energy intensity, increased emissions or insufficient labor productivity. The “low efficiency” group (0,5–0,74) comprises twenty-six regions, the problem of their efficiency is a complex one, mainly energy-environmental, with critically low efficien-cy indicators for some components.Conclusion. This article presents an assessment of the differentiation of the regional economy efficiency by using an integral indicator, taking into account the performance of the use of labor, physical capital, fuel and energy resources and environmental impact. Firm con-clusions on the choice of the method for aggregating particular performance criteria into one generalizing indicator have not been obtained. A practical approach is to solve such problems Economic statistics by different available methods to compare results and to obtain consistent conclusions. Four basic criteria of the regional economy efficiency were taken into account, but methodically their number is not limited and can be increased. The results can be used in the system of mon-itoring and strategic planning of regional economy development. The proposed methodical approach is applicable to other practical tasks of multi-factor comparative analysis of regional development.

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“…If we consider the approaches used for making forecasts of the socio-economic development of systems, it is possible to see that the proposed toolkit is quite diverse. Primarily these are well-known econometric models [1]. Various neural network models are popular today [2].…”

Section: Introductionmentioning

confidence: 99%

Regression-matrix Model and Its Application in Socio-economic Foresight

Davnis¹,

Панкова²,

Shulgina³

2019

Proceedings of the 2nd International Conference on Economy, Management and Entrepreneurship (ICOEME 2019)

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This paper proposes a regression-matrix model for predicting the socioeconomic development of regional systems. The ability to build up such a model provides for the classification of indicators into groups depending on their socioeconomic purpose. The structured data presentation has led to the prerequisite for a graded construction of models that ensure a proactive balance of the dynamics at two levels: cluster-type and system-based. According to the assumption, group balance should ensure the consistency of the expected growth of each indicator with the group dynamics of the corresponding block. The systemic balance is provided by the introduction of group dynamics indicators in the form of principal components, in turn, the regression-matrix approach is applied.

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Modeling the Development of Regional Economy and an Innovation Space Efficiency

Cited by 24 publications

References 4 publications

Assessing The Impact Of Resource Potential On The Results Of Agricultural Activity

Assessing The Impact Of Resource Potential On The Results Of Agricultural Activity

Differentiation of the economic efficiency in the regions of Russia

Regression-matrix Model and Its Application in Socio-economic Foresight

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