In the context of spatial heterogeneity in modeling innovative processes, the research of spatial mutual influences becomes relevant. The aim of our study is to assess the spatial features of innovative development of Russia’s regions and to simulate spatial effects, resulting from the impact of surrounding territories. The work uses methodological approach, based on systematic use of various tools of spatial econometrics and distance measurement systems: 1) spatial autocorrelation analysis according to the methodology of P. Moran; 2) formation of L. Anselin’s matrix of local indices of spatial autocorrelation (LISA) by different types of weighting matrices of distances between regions; 3) construction of the spatial Durbin model, which takes into account the presence of spatial lag of the resultant attribute (volume of shipped innovative goods, works performed and services rendered) and key factors (volume of expenditures on innovative activities of organizations, number of total personnel engaged in research and development). The novelty of the presented methodological approach lies in the systematic use of spatial econometric tools (spatial autocorrelation analysis and spatial autoregression), different measurement distance systems between regions (spatial weighting matrices). When building regression models, we took into account official statistical data of the Federal State Statistics Service for 78 Russia’s regions for the period from 2000 to 2021. As the research results, using the Durbin model, we established a positive impact of financial resources allocated by enterprises within the region on innovation activity, and at the same time, their negative impact on the dynamics of shipped innovative goods in neighboring regions, which is associated with possible outflow of financial resources to pay for the resources necessary for effective innovative development. Regions with low level of innovation activity have advantages of neighborhood with developed innovative centers in terms of access to R&D personnel and scientific infrastructure
Keywords
innovative development, Russia’s regions, spatial effects, spatial Durbin model, spatial autocorrelation analysis