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

РАЗРАБОТКА ПОДХОДА К ОЦЕНКЕ ОТНОСИТЕЛЬНОЙ СИЛЫ МЕХАНИЗМОВ АГЛОМЕРАЦИОННЫХ ЭФФЕКТОВ В РОССИИ НА ОСНОВЕ МИКРОДАННЫХ О РОССИЙСКИХ ПРОИЗВОДИТЕЛЯХ И МУНИЦИПАЛЬНЫХ ОБРАЗОВАНИЯХ

Rostislav, Konstantin (Ростислав, Константин), Ponomarev, Yuriy (Пономарев, Юрий) () and Radchenko, Darina (Радченко, Дарина)
Additional contact information
Rostislav, Konstantin (Ростислав, Константин): The Russian Presidential Academy of National Economy and Public Administration
Ponomarev, Yuriy (Пономарев, Юрий): The Russian Presidential Academy of National Economy and Public Administration
Radchenko, Darina (Радченко, Дарина): The Russian Presidential Academy of National Economy and Public Administration

Working Papers from Russian Presidential Academy of National Economy and Public Administration

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.

Keywords: agglomerations; agglomeration effects; mechanisms; boundary delimitation; machine learning (search for similar items in EconPapers)
JEL-codes: C02 R1 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2022-11-10
New Economics Papers: this item is included in nep-cis, nep-com, nep-mac and nep-ure
References: Add references at CitEc
Citations:

Downloads: (external link)
https://repec.ranepa.ru/rnp/wpaper/w20220295.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rnp:wpaper:w20220295

Access Statistics for this paper

More papers in Working Papers from Russian Presidential Academy of National Economy and Public Administration Contact information at EDIRC.
Bibliographic data for series maintained by RANEPA maintainer ().