Abstract

The aim of this article. The aim of this article is to identify and check how the selected macroeconomic factors are affecting the fluctuation of economic processes. According to the theory of RBC, the real economic shock could be an indirect factor that reflects the introduction of modern technologies; this fact could affect the cycle fluctuations. The results of the analysis. During the last century there were many theories of economic cycles. Each theory has its supporters and critics. But, the youngest and the most controversial is real theory of the business cycle (RBC). According to this model, the main driver of economic growth is the increasing of investment and research and development spending as well as in human capital. Ups and downs of the economy could be a specific response to unexpected shocks in the real business environment. In accordance with the tasks in the paper, it is necessary to identify and verify the macroeconomic factors that influence the fluctuations of economic processes. In addition, according to the RBC theory, there should be assessed an indirect indicator that reflects the development of modern technology. To test the impact of modern technologies on the fluctuations of GDP (the main material for the research) there was adopted economic performance of European Union (EU). The EU has the highest level of economic development in the world; its GDP in 2014 was $18,5 trillion. The EU statistics indicate its level of technology and communications, one way of measurement of their development is index of ICT. The index is a synonym for «information technology» and used by the UN International Telecommunication Union. The analyzed period is 2000-2013 years. During this period, 15 new member states have joined the EU. The main components of GDP by expenditures include final consumption of households, gross capital formation (investment), government spending and net exports. Since there is no direct component to determine the impact of innovative technologies adopted, the indirect indicator that defines research and development R&D was added into the model. There are 5 variables in this model in total. From the five macroeconomic indicators for each of 28 countries of the EU for 16 years, balanced panel data was established. The table contains 448 rows (28 countries and 16 years) and 2688 different values. In order to separate the cyclical component from the introduced analytical data the Hodrick-Prescott filter was used. To calculate the data, there was used program EViews 8. To control the accuracy of the calculations and to determine whether the collected data contains unwanted processes such as unit roots, autocorrelation or heteroskedasticity all tests were conducted. In addition, all the values were filtered in order to reduce the price changing effects. Conclusions and opportunities of further researches. Excluding of possible unwanted structural processes suggests that the results are adequate and very credible. The results obtained shows that the change in consumption by 1% causes a change in the cyclical component of GDP by -5,78%. This will lead to a reduction in future investments that will influence fluctuations negatively as the result. In the case of government expenditures the result is also negative, but it could be explained by the RBC theory. Despite the fact that government spending is one of the largest part of GDP, it does not significantly affect its volatility. The highest impact on GDP volatility in this model makes investment. Whenever the factor changes by 1%, the cyclical reaction will be a change by 9,5%. For every change in net exports by 1%, the cyclical component of the GDP changes by 0,68%. Every time the R&D expenditure is changing by 1%, fluctuation is changing by 1,87%. The calculations and testing shows that according to the theory of RBC and estimation of the model, the gross capital formation and research and development expenditure are the key factors of increasing growth of the European Union economy.

Keywords: GDP, RBC theory, macroeconomic factors, innovative technologies, economic process, mathematical modeling, econometric estimation

JEL Classification: E22, E29, E62, C23.

Cite as: Savchenko, S. (2015). The impact of macroeconomic factors on the fluctuation of economic processes. Marketing and Management of Innovations, 2, 193-200. https://doi.org/10.21272/mmi.2015.2-16

This work is licensed under a Creative Commons Attribution 4.0 International License

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