Impact of Research and Innovative Activity on Russian Regions’ GRP: Correlation and Regression Analysis

To improve the effectiveness of strategic management of Russian regions scientific and innovative development, it is important to understand the patterns of its mutual influence with the level of regional economies. Based on multiple regression analysis, significant correlations were identified between economic indicators and parameters of scientific and innovative activities. The study is based on correlation and regression analysis. The dataset analyzed covers 77 regions of Russia, excluding 8 sparsely populated regions whose economies are most significantly associated with mining, as well as 75 regions from this sample, but excluding Moscow and St. Petersburg. Since sanctions against Russia in 2022 created barriers to the publication activity of Russian scientists in internationally represented journals, an array of indicators of scientific and innovative activity for 2021 was used, including the number of publications in Scopus by scientists in the regions of the Russian Federation and data from the Science and Innovation section from the regional collection of Rosstat. There is a significant positive correlation between scientific and innovative activity and the Russian regions GRP. The most significant factor turned out to be the indicator of publication activity in the field of economics, econometrics and finance. The model explains 68% of the variation in GRP per capita by region, which indicates the importance of scientific and innovative activity for economic growth. The obtained regression formula shows that only at a certain level of economic development scientific and innovative activity begins to have a significant impact on economic growth. This is important for taking into account the spatial distribution of scientific potential in the management processes. The formula generally provides a certain “strategic recipe” for scientific and innovative development of a Russian region: support for research into specific economic problems, development of applied science that solves specific production or other problems, as well as the desire to produce innovative products. This result can be used in the formation of scientific and innovative components of regional development strategies.

1. Betarelli A.A, Faria W.R., Montenegro R.L.G., Bahia D.S., Gonçalves E. (2020) Research and Development, Productive Structure and Economic Effects: Assessing the Role of Public Financing in Brazil. Economic Modelling. Vol. 90. P. 235–253. DOI: 10.1016/j.econmod.2020.04.017

2. Caporale G.M., Rault C., Sova A.D., Sova R. (2015) Financial Development and Economic Growth: Evidence from 10 New European Union Members. International Journal of Finance and Economics. Vol. 20. Is. 1. P. 48–60. DOI: 10.1002/ijfe.1498

3. Darda E.S., Ustinov E.A. (2016) Faktory razvitiya fondovogo rynka rossiyskoy federatsii: statisticheskaya otsenka [Factors in the development of the stock market of the Russian Federation: Statistical assessment]. Innovatsii i investitsii. No. 10. P. 70–74.

4. Fraumeni B.M. (2022) Gross Domestic Product: Are Other Measures Needed? IZA World of Labor. DOI: 10.15185/izawol.368.v2

5. Gobernik N.S., Mityakov S.N. (2013) Method of Assessment of Innovation Activity Impact of Industrial Organizations on Their Development. Statistika i ekonomika. No. 1. P. 32–35.

6. Goridko N.P., Nizhegorodtsev R.M., Olisaeva O.L. (2011) Regression Analysis of Factors for Economic Growth of the Region as an Instrument to Reveal Key Directions of Macroeconomic Adjustment. Izvestiya Volgogradskogo gosudarstvennogo tekhnicheskogo universiteta. No. 14(87). P. 164–177.

7. Goridko N.P., Nizhegorodtsev R.M. (2011) Fenomen «rosta na ozhidaniyakh»: regressionnyy analiz i relyativistskaya kontseptsiya vremeni v ekonomiki [The phenomenon of “growth on expectations”: Regression analysis and the relativistic concept of time in the economy]. Vestnik ekonomicheskoy integratsii. No. 12. P. 11–27.

8. Gusarova O.M., Kuzmenkova V.D., Komarov P.I. (2018) Digital Model of Socio-Economic Development of Regional Actors. Fundamental’nyye issledovaniya. No. 8. P. 42–47.

9. Henderson V., Storeygard A., Weil D.N. (2011) A Bright Idea for Measuring Economic Growth. American Economic Review. Vol. 101. Is. 3. P. 194–199. DOI: 10.1257/aer.101.3.194

10. Herzer D. (2022) The Impact of Domestic and Foreign R&D on TFP in Developing Countries. World Development. Vol. 151. DOI: 10.1016/j.worlddev.2021.105754

11. Kharitonova D.E. (2016) Korrelyatsionno-regressionnyy analiz v ekonomike [Correlation and regression analysis in economics]. Kontentus. No. 8(49). P. 176–179.

12. Kozinova K.T. (2016) Econometric Analysis of Gross Domestic Product of Russia and Its Relations to Investment in Fixed Assets, Volume of Employment in the Economy, and Oil and Gas Production. Ekonomicheskiy analiz: teoriya i praktika. No 2(449). P. 183–196.

13. Kravtsov A.A. (2017) Development of the Patent-Based Researches on Innovation Processes: Analytic Review. Zhurnal novoy ekonomicheskoy assotsiatsii. No. 3(35). P. 144–169. DOI: 10.31737/2221-2264-2017-35-3-7

14. Krupko A.E., Fetisov Yu.M., Rogozina R.E. (2018) Interpretation of Correlation and Regression Analysis of the Main Factors of Economic Development of the CFD. FES: Finansy, Ekonomika. Vol. 15. No. 12. P. 22–29.

15. Kryzhanovskaya O.A., Stepanova A.R. (2019) Analysis of the Main Trends in the Development of Small Business in the Russian Federation. Teoriya i praktika servisa: ekonomika, sotsial’naya sfera, tekhnologii. No. 4(42). P. 14–18.

16. Mityakov S.N., Mityakov E.S., Mityakova O.I., Yakovleva G.N. (2021) Regional Innovation Assessment Toolkit: Correlation-Regression AnalysIs. Innovatsii. No. 1(267). P. 60–67. DOI: 10.26310/2071-3010.2021.267.1.009

17. Murashova N.A. (2020) Metodologicheskiye osnovy obespecheniya innovatsionnoy deyatel’nosti ekonomicheskikh sistem [Methodological foundations for ensuring innovative activities of economic systems]. N. Novgorod: Nizhegorod. gos. tehn. un-t. im. R.E. Alekseeva.

18. Pozdeev V.L. (2005) Metody otsenki finansovoy ustoychivosti predpriyatiy [Methods for assessing the financial stability of enterprises]. Ekonomicheskiy analiz: teoriya i praktika. No. 24(57). P. 54–58.

19. Soete L., Verspagen B., Ziesemer T.H.W. (2022) Economic Impact of Public R&D: An International Perspective. Industrial and Corporate Change. Vol. 31. Is. 1. P. 1–18. DOI: 10.1093/icc/dtab066

20. Zhang L., Fargher N. (2022) Aggregate Accounting Earnings, Special Items and Growth in Gross Domestic Product: Evidence from Australia. Accounting and Finance. 2022. Vol. 62. Is. 2. P. 2467–2496. DOI: 10.1111/acfi.12871