Contents |
Authors:
Inna Tiutiunyk, ORCID: https://orcid.org/0000-0001-5883-2940 Sumy State University (Ukraine) Andrii Zolkover, ORCID: https://orcid.org/0000-0002-8176-1850 Kyiv National University of Technologies and Design (Ukraine) Vladyslav Maslov, ORCID: https://orcid.org/0000-0002-2241-6424 Banking University, Ukraine Mehriban Samedova, ORCID: https://orcid.org/0000-0002-7022-0936 Azerbaijan State University of Economics (Azerbaijan) Natalia Vynnycenko, ORCID: https://orcid.org/0000-0002-6730-4629 Sumy State University (Ukraine) Yevgenia Beshley, Entrepreneur (Canada) Olena Kovalenko, Entrepreneur (Irland)
Pages: 26-40
Language: English
DOI: https://doi.org/10.21272/mmi.2020.4-02
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Abstract
The article focuses on the study of causal links between the level of innovation development and the shadow economy on the example of 10 European countries. Based on the analysis of existing approaches to determining the level of innovation activity in the country, a linear model for evaluating the Complex Innovative Activity Index is proposed. The main hypothesis of the paper was the assumption that the increase in the level of the shadow economy is accompanied by a decrease in the country’s innovative development, deteriorating access to financial resources, and so on. The purpose of the paper is to analyze the correlation between the level of the shadow economy and the indicators of innovative development of the country as components of its macroeconomic stability using Panel data analysis from 2007 to 2018. Unlike previous studies, this research considered that level of innovative development increasingly depends on the level of the shadow economy. The results confirm the relationship between factor and result indicators for all analyzed countries. To test the hypotheses about the negative impact of the shadow economy on the level of innovative activity of the country was presented the linear model with Complex Innovative Activity Index as an integral indicator of 8 international indexes (Global Competitiveness Index, Digital Readiness Score, Digital Economy and Society Index, Knowledge Economic Index, The European Innovation Scoreboard, Bloomberg Innovation Index, The International Innovation Index, Global Innovation Index) characterizing the level of innovative development of the country. In the second stage: testing of the data series for stationarity by the Dickey-Fuller and Philips Perron test Statistics, calculation of the optimal lag length from the maximum possible selected by the Akaike criteria, the Hannan-Quinn Information Criterion and the Schwartz Information Criterion, verification of cointegration of data series using Johansen test are performed. Empirical calculations have proved the high impact of the shadow economy on the innovative development of the country. All indices are statistically significant at the level of 1% and 5% and 10% respectively. It is substantiated that the state should take into account interdependencies as a basis for the development and implementation of measures aimed at increasing the innovative activity of economic entities, increasing the innovation potential of the country, and so on.
Keywords: innovative activity, investment flows, macroeconomic stability, shadow economy, indices.
JEL Classification: H20, H71, F49, K34.
Cite as: Tiutiunyk, I., Zolkover, A., Maslov, V., Vynnychenko, N., Samedova, M., Beshley, Y., & Kovalenko, O. (2020). Indices of innovation activity as components of macroeconomic stability: how does the shadowing of investment flows affect? . Marketing and Management of Innovations, 4, 26-40. https://doi.org/10.21272/mmi.2020.4-02
This work is licensed under a Creative Commons Attribution 4.0 International License
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