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Clustering methodology of the Russian Federation regions with account of sectoral structure of GRP

Author

Listed:
  • Aivazian, Sergei

    (CEMI RAS, Moscow, Russia)

  • Afanasiev, Mikhail

    (CEMI RAS, Moscow, Russia)

  • Kudrov, Alexander

    (CEMI RAS, Moscow, Russia)

Abstract

The methodology to identify similar groups of Russian regions is presented, each of which has its own model of productive capacity, which determines the dependence of the GRP from the fixed assets and number of employees. It is carried out to test the hypothesis that the parameters of the functions describing the production potential of the regions included in the different groups, different by reason of the sectoral structure of GRP. The procedure for constructing the auxiliary integral indicators based on component analysis is offered, it is reflected the specialization of regions. Developed and tested on data for the period 2009–2013 algorithm of forming a similar group of regions. It is revealed the presence of a greater sensitivity to changes in GRP value of fixed assets for the group of regions with a specialization in mining and mixed type specialty than for groups of regions specializing in manufacturing and agriculture. At the same time, last two groups of regions and the group of regions with emerging economies are more sensitive to changes in the number of employees. The developed methodology is an element of forecasting procedures and planning options for sustainable socio-economic development of regions of the Russian Federation.

Suggested Citation

  • Aivazian, Sergei & Afanasiev, Mikhail & Kudrov, Alexander, 2016. "Clustering methodology of the Russian Federation regions with account of sectoral structure of GRP," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 41, pages 24-46.
  • Handle: RePEc:ris:apltrx:0283
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Mikhail Y. Afanasyev & Alexander V. Kudrov, 2021. "Economic Complexity, Embedding Degree and Adjacent Diversity of the Regional Economies," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 17(2), pages 7-22.
    2. Tetyana Odintsova, 2018. "Influence of Tax Burden on Economic Development of Regions: The Cluster Approach," Oblik i finansi, Institute of Accounting and Finance, issue 1, pages 114-123, March.
    3. Aivazian, Sergei & Afanasiev, Mikhail & Kudrov, Alexander, 2019. "Indicators of the main directions of socio-economic development in the space of characteristics of regional differentiation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 54, pages 51-69.
    4. Leonid A. Serkov & Mikhail B. Petrov & Konstantin B. Kozhov, 2022. "Ñluster-based econometric analysis to study the heterogeneity of Russian regions," Journal of New Economy, Ural State University of Economics, vol. 22(4), pages 78-96, January.
    5. Valentina S. Antonyuk & Elmira R. Vansovich & Anastasiya S. Lapo, 2020. "Transformation in industrial specialization and features of economic development across the subjects of the Russian Federation," Journal of New Economy, Ural State University of Economics, vol. 21(1), pages 72-88, March.
    6. Aivazian, Sergei & Afanasiev, Mikhail & Kudrov, Alexander, 2018. "Indicators of economic development in the basis of the characteristics of regional differentiation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 50, pages 4-22.
    7. Айвазян С.А. & Афанасьев М.Ю. & Кудров А.В., 2016. "Модели Производственного Потенциала И Оценки Технологической Эффективности Регионов Рф С Учетом Структуры Производства," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 52(1), pages 28-44, январь.
    8. Solosina, M. I. & Shchepina, I. N., 2020. "Analytical Tools for Economic Research of Small Municipalities and Gaming Techniques for Community Involvement (the Case of Voronezh Region in Russia)," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 6(2), pages 111-124.

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    More about this item

    Keywords

    regional economy; production potential; econometric modeling; hypothesis testing;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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