Institute of Sociology
of the Federal Center of Theoretical and Applied Sociology
of the Russian Academy of Sciences

Sitkovskiy A.M., Raisikh A.E., Gladky A.S., Bezverbnaya N.A. (2025). The influence of the agglomeration effect on the demographic policy of territories. Economic and Social Changes: Facts, Trends, Forecast, 18(6), 90–109. DOI: 10.15838 ...



Sitkovskiy A.M., Raisikh A.E., Gladky A.S., Bezverbnaya N.A. (2025). The influence of the agglomeration effect on the demographic policy of territories. Economic and Social Changes: Facts, Trends, Forecast, 18(6), 90–109. DOI: 10.15838/esc.2025.6.102.4.
ISSN 2312-9824
DOI 10.15838/esc.2025.6.102.4

Posted on site: 13.01.26

Текст статьи на сайте журнала URL: http://esc.isert-ran.ru/article/30485 (дата обращения 13.01.2026)


Abstract

In the context of increasing spatial polarization and uneven urbanization, the central question becomes the empirical assessment of the agglomeration effect's influence on the demographic dynamics of peripheral settlements. This study is devoted to a quantitative analysis of the relationship between the distance of peripheral settlements from the core of an urban agglomeration and changes in their population during the 2010–2021 intercensal period. The theoretical and methodological basis is formed by the concepts of center-periphery systems and spatial polarization. The research covers 40 urban agglomerations in Russia and is based on studying the demographic dynamics of about 25,000 settlements. The methodology included: determining the geodesic distances from each peripheral settlement to the corresponding core; calculating four metrics of demographic dynamics: absolute, relative, logarithmic growth, and average annual growth rate; estimating paired Pearson and Spearman correlation coefficients between distance and demographic indicators. The empirical data is based on the results of the 2010 and 2020 All-Russian Population Censuses. Overall, for the entire set of peripheral settlements, a weak but stable negative monotonic dependence was recorded. Based on the analysis results, agglomerations were divided into three groups: those with a strong negative gradient (18 agglomerations, predominantly in Siberia and the Urals), a moderate gradient (15 agglomerations, including the largest ones – Moscow and Saint Petersburg), and no significant gradient (7 agglomerations). No positive correlations were found in any case. The practical significance of the results lies in substantiating the priorities of demographic policy: the need for targeted support of remote zones, the development of sub-centers, and the consideration of transport accessibility.