International theoretical and empirical studies have shown that regional development and economic growth largely depend on spatial and non-spatial proximity of regions, which generates knowledge spillovers. We developed a methodological approach to measuring and visualising spatial and structural-technological proximity affecting regional knowledge spillovers. Moreover, we tested the techniques of the cartographic visualisation of the proximity of Russian regions. Further, we analysed foreign and domestic approaches to studying spatial and non-spatial proximity and obtained new results. We described the stages constituting a methodology for the quantitative assessment of different types of regional proximity. Additionally, we proposed a method for constructing a typology of regions based on the coefficients of the non-spatial proximity matrix, calculated according to the indicator “gross value added” for 15 sectors of the Russian National Classifier of Economic Activities (OKVED) for Russian regions. Using the data for the Novosibirsk region in 2005 and 2016, we applied methodological techniques for measuring and visualising geographical and structural-technological proximity (STB) of a region in relation to other constituent entities of the Russian Federation. The Novosibirsk region is located in the middle of the country and has a diversified structure of economic activities and science. For this particular region, there has been an increase in the likelihood of the emergence of knowledge spillover channels with various European regions of Russia and some regions of the Urals and the Far East. Proximity matrices can be used in econometric studies to test hypotheses about the impact of different forms of proximity on regional economic growth. Recommendations to enhance knowledge spillover coincide with the proposals to support the areas of innovative development stated in The Strategy of Spatial Development of the Russian Federation for the period until 2025.
Phenomenon of Structural-Technological Proximity and Knowledge Spillovers between Russian Regions