DEVELOPMENT OF AN APPROACH TO ASSESSING THE RELATIVE STRENGTH OF AGGLOMERATION EFFECTS MECHANISMS IN RUSSIA BASED ON MICRODATA ON RUSSIAN PRODUCERS AND MUNICIPALITIES

Abstract

The development of agglomerations in Russia is a priority of spatial policy. To enhance agglomeration effects and accelerate the growth of the Russian economy it is necessary to understand the mechanisms of agglomeration effects. To compare the strength of Marshall agglomeration effects using the Ellison-Glaser-Kerr approach, the degree of concentration of Russian industries was measured using data on all organizations without exception as of January 1, 2020. The estimates show that pairs of industries in Russia tend to be dispersed relative to each other: most industries have significantly lower concentration than would be expected based on the overall location of these industries. On average, of the three external benefits of concentration according to Marshall, Russia's large labor market is the most important. Proximity to suppliers/buyers, their diversity is least related to the placement of industries in the same areas. The example of Kaliningrad region shows that regardless of the method of selection of organizations for comparison, there is no truncation of the distribution traits. Although the choice of the geographical unit of observation determines the estimation of the strength or even direction of the net agglomeration effects, the general conclusion about the lack of selection of enterprises, which we could take for the benefit of concentration, was unchanged. To verify this conclusion, we used various methods of territorial grouping of enterprises and the boundaries of clusters (agglomerations) of enterprises were estimated using the DBSCAN method. The resulting estimates of the relationship of concentration to various sources of its external benefits support those public policies that seek to encourage the development of large urban agglomerations with large and constant markets for skilled labor. When forming particularly dense clusters, it is advisable to set activity requirements for areas with a special entrepreneurial regime, which would be consistent with estimates of the intensity of possible knowledge exchange between industries.

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