Assessment of the Spatial Heterogeneity of Economic Activity in the Municipalities of Sverdlovsk Oblast

Uneven socio-economic development of municipalities in various regions depends on many factors, in particular, on the peculiarities of the distribution of economic entities and their activities. We hypothesise that this heterogeneity increases due to unequal distribution of labour and investment resources. In order to test this hypothesis, the study assesses the impact of the distribution of personnel and investment resources in the municipalities of Sverdlovsk oblast on the spatial heterogeneity of economic activity. To this end, the methods of regression and spatial autocorrelation analysis were used. The developed methodology involves assessing the spatial heterogeneity of economic activities of various enterprises in territorial systems. Spatial regression analysis was applied to examine the impact of labour and investment resources on the heterogeneity dynamics, while spatial autocorrelation analysis was used to consider the distribution of these factors. Due to the systematic use of spatial autocorrelation analysis for various spatial weights matrices, as well as regression analysis based on panel data and geographically weighted regression, the degree of the influence of factors on the heterogeneity of economic activities in certain municipalities was established. Testing of the presented methodology revealed a trend towards an increase in the spatial heterogeneity of economic activity, its concentration in Ekaterinburg, Nizhny Tagil, Kamensk-Uralsky, as well as in Verkhnyaya Pyshma, Pervouralsk, Verkhnesaldinsky, Polevskoy, Revda, Kachkanarsky, Berezovsky, Zarechny and Serovsky urban okrugs in the period from 2017 to 2020. The Cobb-Douglas model showed that the main factor contributing to the increase in the spatial heterogeneity of the economic entity activity is labour costs; the volume of attracted investments plays an important role in municipalities with a high concentration of shipped goods and rendered services. Based on the model modified using geographically weighted regression, the study established a degree of spatial influence of the examined factors on the economic activity and, together with a spatial autocorrelation analysis of the distribution of human resources and investments in the municipalities of the region, to confirm the hypothesis put forward.