Cluster-Econometric Analysis of Russian Regions: Implications for Differentiated Economic Policys

Abstract

In a rapidly changing economic landscape, a crucial challenge for state economic policy is the need for a differentiated approach to regional development. Despite its importance, this aspect has been insufficiently explored within the framework of macroeconomic regulation. This study investigates regional identity through the unique configurations of economic, innovative, technological, and transport potentials, and their influence on economic growth. At the first stage, a cluster analysis was performed to classify Russian regions into eight groups, based on 27 economic and structural indicators. These indicators encompass various dimensions such as economic capacity, innovation, technological readiness, and transport infrastructure. In the second stage, multiple regression analysis was used to evaluate the effect of these factors on per capita gross regional product. The econometric modelling revealed key drivers of regional growth and identified the factors most significantly influencing development. Analysis of each cluster highlighted the varying degrees of factor potential and future development prospects. The findings suggest that many regions are not fully exploiting their available resources, while some are facing significant constraints to growth, underscoring the need for technological transformation. The study proposes an interregional cooperation policy aimed at redistributing technological capabilities and fostering technology transfer. This approach can help policymakers design more effective economic policies that promote sustainable growth, improve technological development, and balance regional potential.