This research substantiates the expediency of introducing the instruments of neural network theory to the economic practice, since it appears to be a strong mathematical instrument and an alternative to the mathematical approaches currently known. The article suggests and presents a neural network model to forecast the innovative and scientifictechnical development of the Ukrainian economy. The computerized modeling of the adapted neural network has been performed on the basis of Statistica Neural Networks (StatSoft Inc.) package. Taking into consideration the development of the leading countries of the world and Ukraine, this neural network model is based upon the indices reflecting basic results of the state social and economic, innovative, scientific and technical policy within the period of 2000-2013. The suggested technique allows determining the factors that have the greatest influence on the GDP of the country and predetermine its economic development. Among the considered factors, the greatest influence on the GDP growth is made by the amounts of Research and Development (R&D) financing. Not less important for the economic growth is the increase of investments in the basic capital. Among the factors, the least influence on GDP is made by the national budget expenditures on the innovative activity of enterprises. The received predictive data may provide the basis for working out a strategy of the innovative development of the country and regions, investment and innovative programs and budgets.
CITATION STYLE
Yurynets, Z. (2016). Forecasting model and assessment of the innovative and scientific-technical policy of Ukraine in the sphere of innovative economy formation. Investment Management and Financial Innovations, 13(2), 16–23. https://doi.org/10.21511/imfi.13(2).2016.02
Mendeley helps you to discover research relevant for your work.