Identification of high-tech industry clusters at the level of Russian regions and cities in 2015–2019

The general understanding that the maximum effect of economic, especially high-tech activities is achieved in places of their concentration, including in clusters, makes the economic policy of supporting clusters extremely important. At the same time, there is a problem of how to identify clusters deserving of such support. There are relatively few studies suggesting methods for identifying the clusters. The article proposes and tests the author’s methodology for identifying clusters of high-tech industries based on the calculation of a clustering index. It consists of four components associated with the most important characteristics of clusters, i. e. the geographical concentration of the industry in a region or city, their specialization, communications and competition of companies. The index is calculated as the arithmetic mean of the indicators characterizing these components, normalized by the methods of linear and logarithmic scaling. The methodology is applied at two scale levels, namely regions of Russia and their administrative units. Calculation of the index is based on SPARK data on companies for the period 2015–2019. The results of index calculations were verified in order to identify clusters. As a result of the study, differences in high-tech industries were revealed both in terms of the clustering index and its individual components. From a geographical point of view, clusters of high-tech industry were found not only in the regions with the largest urban agglomerations (mainly Moscow and St. Petersburg) with considerable research and entrepreneurial potential, but also in the regions with large high-tech industry enterprises (Volga and Ural regions). It was also found that clusters in different industries have different territorial structure and scale. In most industries they appear at a city level, but in some industries they have a regional scale. Comparison of the identified clusters with those supported by the government made it possible to conclude that among the identified clusters about 35% receive such support, while among the supported clusters about 50% correspond to identified clusters. Besides, the level of support varies between the industries.

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