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December 2017 (published: 20.12.2017)
Number 4(31)
Home > Issue > The methods of forecasting of innovative potential
of the national economy of Russia
Zueva O.A., Kljuzhev N.A.
In the work the authors propose the methods for forecasting mutual variations in incremental results (innovation potential and GDP) and factors (five elements of innovation potential), taking into account their statistical convergence. It has novelty and relevance, because it has no analogues and reproduces a new complex approach in the applied use of the multifactorial linear regression model. The novelty of the technique under consideration is the representation and the method of solving the direct and inverse problems of linear regression. A direct task for a certain increment in the selected component of the innovative potential makes it possible to measure the projected increment in the level of innovation potential and GDP, as well as an increase in other elements of the innovative potential that are statistically interrelated with it. The application of this methodology proves the structuredness and visibility of the decision management process based on the quantitative model of multifactorial linear regression, imparts objectivity and validity for its use in regulating the national economy of Russia with the aim of increasing the level of innovation potential and its elements, and securing significant rates of economic growth. The considered methodology informs about the presence of divergence of real and financial sectors, scientific and high-tech subsectors on the basis of the proposed hypothesis and the need for convergence.
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Keywords: innovative potential, convergence, divergence, real sector, financial sector, scientific subsector, high-tech subsector, national economy.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
UDC 330.101.541
The methods of forecasting of innovative potential
of the national economy of Russia
In the work the authors propose the methods for forecasting mutual variations in incremental results (innovation potential and GDP) and factors (five elements of innovation potential), taking into account their statistical convergence. It has novelty and relevance, because it has no analogues and reproduces a new complex approach in the applied use of the multifactorial linear regression model. The novelty of the technique under consideration is the representation and the method of solving the direct and inverse problems of linear regression. A direct task for a certain increment in the selected component of the innovative potential makes it possible to measure the projected increment in the level of innovation potential and GDP, as well as an increase in other elements of the innovative potential that are statistically interrelated with it. The application of this methodology proves the structuredness and visibility of the decision management process based on the quantitative model of multifactorial linear regression, imparts objectivity and validity for its use in regulating the national economy of Russia with the aim of increasing the level of innovation potential and its elements, and securing significant rates of economic growth. The considered methodology informs about the presence of divergence of real and financial sectors, scientific and high-tech subsectors on the basis of the proposed hypothesis and the need for convergence.
Read the full article
Keywords: innovative potential, convergence, divergence, real sector, financial sector, scientific subsector, high-tech subsector, national economy.
DOI 10.17586/2310-1172-2017-10-4-84-91