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Authors:
Anar Rzayev, ORCID: https://orcid.org/0000-0001-6767-4796 Azerbaijan State University of Economics (Republic of Azerbaijan) Anastasiia Samoilikova, ORCID: https://orcid.org/0000-0001-8639-5282 Sumy State University (Ukraine)
Pages: 133-156
Language: English
DOI: https://doi.org/10.21272/mmi.2020.3-10
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Abstract
The article focuses on the level and dynamics of innovation financing in Azerbaijan and Ukraine compared to the world level and the places of Azerbaijan and Ukraine in the Global Innovation Index and trends in their positioning in the dynamics. The analysis reveals negative dynamics in both countries in this sphere. The innovation financing structure’s role as a factor of economic growth and international reproductive relations development is substantiated. The dependence of the country’s economic growth level (GDP growth per capita) on the value of expenditures on innovation financed by various sectors of the economy (government, the private non-profit sector, foreign investors and the higher education sector) is studied. The study consists of data for 12 European countries for 2007-2017 (limited calculations in 2017 due to the availability of information on open portals of the World Bank, the EU Statistical Office). At the first stage, the distribution of the relevant indicators was evaluated using the Shapiro-Wilk test. Based on these results the method of calculating the correlation coefficient is chosen: Pearson – for indices that are subject to the ordinary distribution law or Spearman – for indices that are not subject to the ordinary distribution law. A correlation analysis regarding the strength and nature of the relationship between relevant indices and the dynamics of GDP per capita in these countries is performed to identify the duration of time lags, after which this relationship is the most statistically significant. In the second stage, there are three types of regression models for estimating panel data to identify the impact on the economic growth dynamics of innovations financed by different economic sectors: 1) with fixed effects (based on the least-squares method); 2) with random effects (based on the general least squares method (GLS); 3) dynamic model for estimation of Arellano-Bond panel data, which considers time lags (based on the general method of moments (GMM)). In the third stage, using Wald’s tests, Breusch-Pagan and Hausman, the adequate model specification is chosen. When choosing a dynamic model of Arellano-Bond, the Sargan test is performed to validate the parameters. The control variables in all three types of models consider net inflows and outflows of foreign investment, inflation (GDP deflator) and labour force participation rate (% of total population ages 15-64). The second and third stages of the study obtained the results as follows. It is empirically confirmed that a 1% increase in the share of government sector-funded R&D expenditures leads to a decrease in annual GDP growth per capita by an average of 0.15% (excluding time), business sector – to the increase by 0.13% with a time lag of 2 years, thanks to foreign sources – to the increase by 0.1% (without time lag); higher education sector – to the decrease by 0.78% (without time lag). It is substantiated that the state should reduce the share of direct investment in innovation. At the same time, it should focus on effective legislation, motivating the business sector and foreign investors to increase investment in research and development to stimulate economic growth in Azerbaijan and Ukraine and the development of international reproductive relations.
Keywords: business sector, correlation analysis, dynamic model, economic growth, financial regulations, financing structure, foreign sources, GERD, government sector, influence formalization, innovation, regression model, R&D
JEL Classification: O4, O3, H5, G32.
Cite as: Rzayev, A., & Samoilikova, A. (2020). Innovation financing structure as a factor of economic growth: cross country analysis. Marketing and Management of Innovations, 3, 133-156. https://doi.org/10.21272/mmi.2020.3-10
This work is licensed under a Creative Commons Attribution 4.0 International License
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