Fertility dynamics differentiated by birth order in Russian regions

Russia is facing one of the most severe demographic problems - low fertility rate. At the same time, fertility dynamics differ significantly across the regions of the country. Subsequently, the birth dynamics of first, second, and subsequent orders also differ. Our study identifies the types of regions that have the same or very similar fertility trends differentiated by birth order. For this purpose, we applied hierarchical cluster analysis based on Ward's method and squared Euclidean distance. We used official Russian statistics and calculated three regional indicators as clustering variables, including the percentage change of the total fertility rate of first, second, and third and subsequent births from 2018 to 2022. We profiled clusters based on economic indicators (gross regional product [GRP], income, and housing provision) and population indicators (women's age at first, second, and third and subsequent births), testing convergent and divergent trends in the dynamics of regional birth rates. Cluster analysis revealed four clusters of Russian regions with similar fertility trends differentiated by birth order. Cluster 1 includes 10 Russian regions and can be considered the most depressive cluster. Cluster 2 includes 18 Russian regions and can be called the driver of Russian population dynamics. Cluster 3, with 38 regions, and Cluster 4, with 19 regions, occupy intermediate positions between the first two clusters. We found no statistically significant differences between the clusters concerning the birth rates that prevailed in 2018; thus, their starting positions did not determine the regional fertility changes in 2018-2022. The analysis revealed that the clusters did not differ in the age of women at first, second, and third and subsequent births. We also did not find statistically significant differences among clusters in terms of the dynamics of economic indicators such as gross regional product, income, and housing provision. The results did not confirm that traditionally recognized economic determinants defined order-differentiated birth dynamics. Russian regions exhibited no convergent or divergent trends in order-differentiated birth dynamics. Our results established new research areas related to the analysis of birth rate determinants, such as informational support for regional programs to increase birth rates. The approach can form the foundation for developing a segmented state information policy in the demographic sphere. It also indicates the need for continuous monitoring of the reasons behind declining birth rates differentiated by birth order and the related stereotypes concerning various socio-demographic population groups.