ИСТИНА

It is well-known that development is uneven across regions. Russia has a signifi-cant scientific, research, innovative potential, efficient use of which will improve the competitiveness of the economy. To analyze the Spatial Concentration of Innovation in Russian regions it was used Gini, Rosenbluth (Tideman-Hall) and Herfindahl-Hirschman indices. The concen-tration of technological costs in certain regions is usually accompanied by growth of divergence. The technological expenditures are less concentrated in the regions, than cost of R & D. The concentration of R & D staff is high enough in the Russian regions and has a tendency to grow. Over 60 % of all scientific staff works in the four leading regions: Moscow city, Moscow region, St. Petersburg and Nizhny Novgorod region. Diversification of regions by types of economic growth is explained largely by the path dependence. Transition from the previous development trajectory through in-novations cannot take place without the necessary prerequisites and shall be formed on the basis of the industrial structures, labour market and institutes already established in the region (Neffke, Henning, Boschma, 2011). To determine path breaking it has been used a method of proximity evaluation between the high-tech sector and the existing structure of industrial production in the region. It differs from the traditional use of the localization coefficient, but not the comparative advantage of the exported product groups. It makes it possible to elimi-nate a number of deficiencies caused by the externalities of the foreign trade, peculiari-ties of the statistical accounting of exporters, and can be suitable for countries with the receptive internal market and/or homogeneous export structure. The calculated prox-imity indexes make it possible to determine such high-tech industries to the develop-ment of which there are the necessary prerequisites in the region, i.e. the technological-ly similar industrial production is under development. We have calculated the indicator of proximity between the industry branches by a number of the employed in 2016. Samples have counted to 198 industrial sub-branches for 83 Russian regions. We have created a matrix of indicators in the industri-al branches 198 х 198, which makes it possible to determine the spatial connections in the branch. A number of pairs of industries not having the connection is 1072 or 5.5%. It is traditionally considered that two economy sectors can be characterized as connect-ed if the proximity index is equal to or exceeds 0.25. In the obtained sample, such con-dition is met by 5690 industry pairs or 29.2%. It was determined that 25% of sub-branches connected with the high technology sector. We made the condition more rigorous and consider a case as connection of branches if the proximity index is more than 0.40. We can see that, firstly, the high-tech branches are connected between each oth-er. Secondly, arrangement of high-tech production in the regions is often accompanied by the logically connected branches (for example, the pharmaceuticals with chemical production). Thirdly, we can distinguish some branches, which are difficult to be logi-cally connected to new technologies, but they have high index of proximity with some of them. So, one of the branches most closely connected to high-tech industry sectors is the production of handbags, similar leather goods and shoes. We have demonstrated that individual regions can progress through investment into in-terregional connections and domestic innovations. These two conditions facilitate une-ven development, decrease dependence on the created industrial structure, make it pos-sible to keep the comparative advantages and get to a completely new path of develop-ment.