The existing body of academic literature reveals that production, distribution, and consumption might be both consistently connected and geographically scattered. This requires assessing the spatial order of production–distribution–consumption cycle, within which exploring of spatial relationship would be based on mutual dependence on each other’s of production, distribution and consumption. Hierarchical and spatial nesting of production, distribution, and consumption data allows us to apply hierarchical spatial autoregressive models (HSAR). The study was conducted on data from 2132 municipalities within 84 regions of the Russian Federation in 2018. The created models enabled distinguishing intraregional and interregional effects and highlighted the positive effect of spatial interactions in production volume. The calculations showed that population income, which determine the demand for goods are positively associated with production volume while relationship between manufacturing and wholesale is negative, resulting in revision of relations between wholesale and manufacturing enterprises and boosting ways of improvement the competitiveness of manufactured goods. The results allow us not only to enhance understanding of the spatial pattern of production–distribution–consumption cycle, but also to reveal new opportunities in the development of supply chain location policy.