Kashepov A.V. Spatial sciences and typology of Russian regions by socio-economic indicators. Bulletin of the Altai Academy of Economics and Law. 2026. No. 6. Pp. 12-19. Kashepov A.V. Spatial sciences and typology of Russian regions by socio-economic indicators. Bulletin of the Altai Academy of Economics and Law. 2026. No. 6. Pp. 12-19.ISSN 2226-3977DOI 10.17513/vaael.4528РИНЦ: https://www.elibrary.ru/item.asp?id=91729873Posted on site: 13.07.26Текст статьи на сайте журнала URL: https://vaael.ru/ru/article/view?id=4528 (дата обращения 13.07.2026)AbstractThe article examines the role and place of typology as a research method in the system of spatial sciences. The expediency of the transition from an a priori (qualitative) typology of territorial socio-economic objects to an automatic typology is substantiated. The author's classification of the regions of the Russian Federation according to 26 socio-economic indicators developed in 2024 is considered as an automatic typology. The typology includes 5 types of regions, which differ in terms of economic development, production structure, level of urbanization, labor productivity, wage level, distance from Moscow, and other characteristics. The types of metropolitan megacities with adjacent regions, the most promising northern regions producing energy resources, other northern and eastern regions with a predominantly extractive profile, old-industrial regions with a processing profile, and predominantly agrarian republics of the North Caucasus and Southern Siberia with a lower level of economic development are distinguished. It is assumed that the typology can be used as an auxiliary tool for analyzing, forecasting and monitoring the socio-economic situation in the regions of Russia, as well as for presenting statistical information in the context of the subjects of the Russian Federation. It is also assumed that it may be advisable to periodically repeat the clustering of the considered socio-economic objects and monitor the status of regions and their possible transitions between classification groups.