The Spatial Autoregression Model of Innovative Development of Russian Regions

Abstract

This work examines the spatial heterogeneity of the innovative development of regional systems and forms a spatial autoregressive model that establishes the factors of its formation and stable inter-regional relationships in innovative development. The article presents a methodological toolkit for constructing a spatial autoregressive model for the innovative development of regional systems, which involves spatial analysis of data using the segmentation of regions by the level of innovative activity and the amount of funding, provision of territories with research personnel, and development of advanced production technologies. This toolkit assumes spatial autocorrelation analysis by the Moran method using various matrices of spatial weights to find the poles of innovative growth, inter-regional spatial clusters, zones of their influence and stable inter-regional relationships in innovative development. It also assumes the formation of a spatial model describing the influence of various factors of internal and external environments on the dynamics of innovative processes. The model, features of spatial clustering of innovative processes at the macroeconomic level, and stable interregional relationships in innovative development, which were established as a result of the study, can be used to construct scenario forecasts for the innovative development of regions and search for optimal management decisions in the implementation of the Spatial Development Strategy of the Russian Federation until 2025.