At the present stage of globalization development, the issues of spatial development of the Russian Federation and its constituent entities bring to the fore the need to develop methodological approaches to identify agglomeration processes in the regions of the Russian Federation. The study is based on our own algorithm for identifying agglomeration processes in spatial economics using Moran’s I. At the first stage of the study (analysis of migration growth in the Russian Federation over a ten-year period), 85 regions of Russia were included in the sample. The second stage (identification of territories involved in the agglomeration process) considered the Moscow Region with the inclusion of Moscow, the Leningrad Region with the inclusion of Saint Petersburg, the Tyumen Region, the Krasnodar Territory and the Kaliningrad Region. The study period covered years from 2012 to 2023. The information base used the data from the Federal State Statistics Service, and linear distances were calculated based on data from the automotive portal. The scientific novelty of the research results lies in the fact that through the assessment of spatial autocorrelation and the use of Moran’s I to identify the degree of connectivity of territories, municipalities involved in the agglomeration process with varying degrees of intensity have been identified. The results obtained can serve as a scientific basis for making effective management decisions by the leadership of Russian regions on the development of agglomeration processes, as well as be used by federal authorities to assess the degree of intensity of agglomeration processes in the spatial economy of the Russian Federation and work out a spatial development strategy
Keywords
agglomeration, migration growth, Moran’s I, population density, spatial autocorrelation, spatial economy