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Estimation of the Spatial Connectivity of the Economic Activity of Russian Regions

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  • E. A. Kolomak

    (Institute of Economics and Industrial Engineering, Siberian Branch, Russian Academy of Sciences
    Novosibirsk National Research State University)

Abstract

— The article examines change in the effects of spatial connectivity of Russian regions’ economic activity for 1997–2016. Quantitative estimates are obtained using spatial econometrics methods. Two specifications of the model are used: the spatial lag model and spatial error model. Relations between regions are modeled through spatial external effects, which are described in two ways: using a nearest neighbor matrix and an inverse distance matrix. The following hypotheses are tested: (1) a single macroeconomic policy and market integration stimulate growth in the spatial connectivity of economic activity; (2) Russia’s western territories have closer spatial ties compared to the eastern; (3) imposition of sanctions against Russia stimulated the formation of new and strengthened existing internal ties, as well as the country’s spatial connectivity. Estimates have shown that there are no distinct trends in the spatial connectivity of economic activity in Russia, nor were interregional interactions affected by international sanctions. Relations important for economic activity are supported mainly with neighboring regions. The cooperation that arises between regions is not deep spatially and fades rapidly with increasing distance. This is also confirmed by the fact that for European Russia, spatial relations are a more significant development factor than for eastern regions.

Suggested Citation

  • E. A. Kolomak, 2020. "Estimation of the Spatial Connectivity of the Economic Activity of Russian Regions," Regional Research of Russia, Springer, vol. 10(3), pages 301-307, July.
    • Handle: RePEc:spr:rrorus:v:10:y:2020:i:3:d:10.1134_s2079970520030089
    DOI: 10.1134/S2079970520030089
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    References listed on IDEAS

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    Cited by:

    1. Xiangyang Cao & Yishao Shi & Liangliang Zhou & Tianhui Tao & Qianqian Yang, 2021. "Analysis of Factors Influencing the Urban Carrying Capacity of the Shanghai Metropolis Based on a Multiscale Geographically Weighted Regression (MGWR) Model," Land, MDPI, vol. 10(6), pages 1-19, May.
    2. B. M. Mukhamediyev & L. S. Spankulova, 2022. "Mutual Influence of Innovation and Human Capital on Regional Growth in Neighboring Countries: The Case of Russia and Kazakhstan," Regional Research of Russia, Springer, vol. 12(3), pages 350-364, September.
    3. N. A. Kravchenko & S. R. Khalimova & A. I. Ivanova, 2021. "Regional Factors in the Development of the ICT Sector in Russia," Regional Research of Russia, Springer, vol. 11(1), pages 91-100, January.

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