Cascade Model of Innovative Dynamics with Investment Flows
Background/Objectives: The article is aimed at identifying interrelations between the technological and investment components of the economic growth and improving the cascade model of the innovation paradigm developed by M. Hirooka. Methods/Statistical analysis: Based on the statistical data on the number of patents, the amount of investment and savings, levels of production and GDP, we will explore the correlation between innovation process, technological change and economic growth. In this study, econometrical analysis of time-series and spectral-temporal analysis with Wigner-Ville distribution are used as research method. Findings: The study found that the required correlation could be represented as Hirooka's cascade model; also, the manner of this correlation was determined. The expanded cascade model augmented by investment flows is proposed to describe the dynamics of macroeconomic development; it consists of a system of differential equations. The findings support the hypothesis of J. Schumpeter and G. Mensch about the evolutionary nature of economic development. A mathematical model of innovation dynamics was suggested, which describes cyclic asynchronous fluctuations in the GDP index against the trend and allows for predicting with a high accuracy the dynamics of the macro-indicator in the short term, as well as for estimating the nearest crisis occurrence timelines. We suppose this result to be of the utmost importance from a practical point of view as it enables to develop economy policy in accordance with upcoming changes. Applications/Improvements: The results of the article can be used in prediction the trajectory of macroeconomic growth.