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ECONOMIC GROWTH MODELING USING NON-LINEAR PREDICTION METHODS

I. Babenko

First published: 2017https://doi.org/10.5593/sgemsocial2017/15/S05.044View metrics

Abstract

Growth models are considered to be interesting to economists. The article shows the analyses of the basic approaches to growth models. Under the conditions of economic uncertainty the theories that take into account non-leaner relationships between development factors are considered to be very powerful. Moreover the solutions to the development factors that form cyclical path and the model based on the use of cyclical nature of economic development can be also very helpful. For this purpose special attention is given to the dynamic models, since leaner nature of relationships can be used to predict economic processes under the circumstances of planned economy. The latter is characterized by stable conditions of economic growth. Under the circumstances of transition-type and market economy, when most of economic processes have unstable nature, leaner models simplify the model, decrease adequacy of dynamic process description. In the course of research development attractors were formed using an example of the Kursk region.

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Publication details

Title
ECONOMIC GROWTH MODELING USING NON-LINEAR PREDICTION METHODS
Authors
I. Babenko
Proceedings
4th International Multidisciplinary Scientific Conference on Social Sciences and Arts SGEM 2017
Publisher
STEF92 Technology
Year
2017
Pages
347-354
SWS Citekey
Babenko20175347354
ISSN
2367-5659
ISBN
978-619-7408-17-1
Language
en
Publication type
Proceedings Paper
Proceedings contents
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Keywords
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