Phenomenon of Structural-Technological Proximity and Knowledge Spillovers between Russian Regions
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 structura...
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| Format: | Article |
| Language: | English |
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Russian Academy of Sciences, Institute of Economics of the Ural Branch
2020-12-01
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| Series: | Экономика региона |
| Subjects: | |
| Online Access: | https://www.economyofregion.com/data/jarticles/3332.pdf |
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| author | Galina A. Untura Maria A. Kaneva Olga N. Moroshkina |
| author_facet | Galina A. Untura Maria A. Kaneva Olga N. Moroshkina |
| author_sort | Galina A. Untura |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T10:22:07Z |
| format | Article |
| id | doaj.art-d330cfcda3eb42b6b1859477a8a3c281 |
| institution | Directory Open Access Journal |
| issn | 2072-6414 2411-1406 |
| language | English |
| last_indexed | 2024-03-12T10:22:07Z |
| publishDate | 2020-12-01 |
| publisher | Russian Academy of Sciences, Institute of Economics of the Ural Branch |
| record_format | Article |
| series | Экономика региона |
| spelling | doaj.art-d330cfcda3eb42b6b1859477a8a3c2812023-09-02T10:02:22ZengRussian Academy of Sciences, Institute of Economics of the Ural BranchЭкономика региона2072-64142411-14062020-12-0116412541271https://doi.org/10.17059/ekon.reg.2020-4-17Phenomenon of Structural-Technological Proximity and Knowledge Spillovers between Russian RegionsGalina A. Untura0https://orcid.org/0000-0002-0987-3137Maria A. Kaneva1https://orcid.org/0000-0002-9540-2592Olga N. Moroshkina2https://orcid.org/0000-0001-5450-1853Institute of Economics and Industrial Engineering of the Siberian Branch of RASGaidar Institute for Economic PolicyInstitute of Economics and Industrial Engineering of the Siberian Branch of RASInternational 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.https://www.economyofregion.com/data/jarticles/3332.pdfrussian regionseconomic growthknowledge spilloversspatial proximitystructural-technological proximitymeasurementvisualisationtypologiesnovosibirsk region |
| spellingShingle | Galina A. Untura Maria A. Kaneva Olga N. Moroshkina Phenomenon of Structural-Technological Proximity and Knowledge Spillovers between Russian Regions Экономика региона russian regions economic growth knowledge spillovers spatial proximity structural-technological proximity measurement visualisation typologies novosibirsk region |
| title | Phenomenon of Structural-Technological Proximity and Knowledge Spillovers between Russian Regions |
| title_full | Phenomenon of Structural-Technological Proximity and Knowledge Spillovers between Russian Regions |
| title_fullStr | Phenomenon of Structural-Technological Proximity and Knowledge Spillovers between Russian Regions |
| title_full_unstemmed | Phenomenon of Structural-Technological Proximity and Knowledge Spillovers between Russian Regions |
| title_short | Phenomenon of Structural-Technological Proximity and Knowledge Spillovers between Russian Regions |
| title_sort | phenomenon of structural technological proximity and knowledge spillovers between russian regions |
| topic | russian regions economic growth knowledge spillovers spatial proximity structural-technological proximity measurement visualisation typologies novosibirsk region |
| url | https://www.economyofregion.com/data/jarticles/3332.pdf |
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