Subject. We explore the housing market of Russian regions during the period of economic turbulence in 2020–2021. Objectives. The purpose is to reveal groups of regions (virtual clusters) with similar values of basic parameters of the housing market, enabling to identify its quality and development directions. Methods. The study draws on methods of economic-statistical, cluster and logical analysis of basic parameters of the housing market of Russian regions. Results. The paper presents results of the economic and statistical analysis of the housing market in Russian regions during the period of economic turbulence in 2020–2021 according to its basic parameters, i.e. per capita income of the population, commissioning of residential buildings per person, rate of natural increase, migration growth rate, the volume of mortgage housing loans. Conclusions. In the housing market during the turbulence of 2020–2021, the regions of Russia formed five groups (virtual clusters), differing in number, spatial localization, and values of basic parameters enabling their identification as follows: (1) an active cluster with elements of risky lending; (2) a cluster with significant untapped potential for the housing market development; (3) a cluster with a high need for the housing market development, which is insufficiently realized due to low level of current incomes of the population and credit resources; (4) a cluster with reduced level of housing market activity and underutilized current incomes and mortgage lending opportunities; and (5) one with the largest housing market constrained by lower incomes.
Keywords: economic and statistical analysis, region, cluster, housing market
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