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The impact of science, innovation and concentration of production enterprises on the economic growth in the Russian regions

Vol. 15, Iss. 12, DECEMBER 2019

Received: 25 September 2019

Received in revised form: 11 October 2019

Accepted: 31 October 2019

Available online: 13 December 2019

Subject Heading: INNOVATION AND INVESTMENT

JEL Classification: C21, O10

Pages: 23272343

https://doi.org/10.24891/ni.15.12.2327

Untura G.A. Institute of Economics and Industrial Engineering, Siberian Branch of Russian Academy of Sciences (IEIE SB RAS), Novosibirsk, Russian Federation
galina.untura@gmail.com

https://orcid.org/0000-0002-0987-3137

Kaneva M.A. Gaidar Institute for Economic Policy, Moscow, Russian Federation
mkaneva@gmail.com

https://orcid.org/0000-0002-9540-2592

Zabolotskii A.A. Institute of Economics and Industrial Engineering, Siberian Branch of Russian Academy of Sciences (IEIE SB RAS), Novosibirsk, Russian Federation
ieie@inbox.ru

https://orcid.org/0000-0003-2683-6116

Subject The article examines how knowledge spillover influences economic factors.
Objectives The study evaluates how the growth rate of GRP per capita responds to the impact of expenditures on S&T, knowledge spillover due to geographical neighborhood, organization of economic activities, concentration and specialization of production enterprises and engineering efforts of people in the Russian regions.
Methods The study relies upon the cross-sectional regression analysis of 80 regions and four sectors of economy by section of the Russian Classifier of Types of Economic Activity (OKVED).
Results In those regions that have the moderate and definite specialization (HerfindahlHirschman index) the growth rate of GRP per capita appeared to be higher than the average of 80 regions. Analyzing economic sectors, we figured out that strong innovative regions had a higher growth rate of GRP per capita as compared to the other regions. Those regions that finance R&D demonstrated a growth in GRP per capita coupled with an increase in engineering efforts.
Conclusions and Relevance Referring to calculations based on the 2013 data, we found the effect generated with a combination of two related groups of growth drivers increasing the growth rates of GRP per capita, i.e. investment in technological innovation and economic structure across regions that feature various economic sectors and industries or concentration of production enterprises. Our conclusions and recommendations are of applied nature with respect to goals set by the Strategy of Spatial Development of Russia.

Keywords: economic growth, innovation, HerfindahlHirschman index, cross-sectional regression

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