Assessing the effect of innovation determinants on macroeconomic development within the EU (28) countries


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Innovations play an inevitable role in achieving macroeconomic growth of countries, and innovative activity is perceived as a source of sustainable development. This paper’s main objective is to explore the impact of innovation determinants on the macroeconomic development of the EU (28) member countries and identify key problem areas distorting sustainable development and growth of these countries. The research analysis is performed using panel data regression models estimated from 2010 to 2018. Innovation potential was quantified using selected indicators, such as patent granted, high-tech exports, gross domestic expenditures on R&D, government expenditure on education, direct investment, gross fixed capital, and tertiary educational attainment. Such indicators as real GDP per capita and GNI per capita were applied to measure economic growth. The results provide evidence of a statistically significant relationship between innovation and economic growth (p < 0.01). Therefore, both research hypotheses were accepted. Based on innovation potential assessment, the statistically significant impact of five indicators were confirmed (high-tech exports, gross domestic expenditure on R&D, government expenditure on education, direct investment, and tertiary educational attainment). In this backdrop, the most significant effect was revealed for variable gross domestic expenditure on R&D (0.5343). The findings lead to the conclusion that the EU’s and national innovation policies and initiatives should aim to create framework conditions that favor the innovation environment and increase R&D expenditure to endorse real economic growth.

This article has been prepared within the research project VEGA No. 1/0279/19 “Model approaches to increase performance and competitiveness in the European area in the context of sustainable development”.

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    • Figure 1. The analysis of the GDPpc and GNIpc average values development in the EU (28) countries
    • Table 1. Overview of the most common indicators used for the country’s innovation potential measurement
    • Table 2. Definition of selected variables entering into analyses
    • Table 3. Descriptive statistics of the selected innovation indicators
    • Table 4. Panel data regression analysis between GDPpc and innovation indicators
    • Table 5. Panel data regression analysis between GNIpc and innovation indicators
    • Funding acquisition
      Dana Kiselakova
    • Investigation
      Dana Kiselakova, Veronika Cabinova
    • Project administration
      Dana Kiselakova
    • Supervision
      Dana Kiselakova, Beata Sofrankova
    • Writing – original draft
      Dana Kiselakova, Beata Sofrankova
    • Writing – review & editing
      Dana Kiselakova, Beata Sofrankova, Erika Onuferova, Veronika Cabinova
    • Conceptualization
      Beata Sofrankova
    • Methodology
      Beata Sofrankova, Erika Onuferova
    • Software
      Beata Sofrankova, Veronika Cabinova
    • Formal Analysis
      Erika Onuferova
    • Resources
      Erika Onuferova, Veronika Cabinova
    • Validation
      Erika Onuferova
    • Visualization
      Erika Onuferova, Veronika Cabinova
    • Data curation
      Veronika Cabinova