CLASSIFICATION OF MATHEMATHICAL MODELS FOR MODELLING THE DYNAMICS OF MACROECONOMIC SYSTEMS
DOI:
https://doi.org/10.31891/mdes/2023-10-26Keywords:
modeling the dynamics of macroeconomic systems, nonlinear dynamics, synergetic approach, decision-making systems, systems of differential equations, discrete iterative mapsAbstract
The complexity of modern economic systems, the nonlinearity of the processes occurring in them, the uncertainty of the external conditions of their functioning requires the application to the study of these systems of a methodological apparatus that would adequately reflect the object of research, allow making reliable forecasts of its development and provide the necessary information for making effective decisions regarding the management of this object. Such a tool is the theory of nonlinear dynamics, which since the 80s of the last century has been widely used in the modeling of natural and technical systems. On the other hand, the use of classical nonlinear dynamic mathematical models, such as, for example, the spider-like model or the Solow model, remains relevant in economic research. This article proposes a classification of mathematical models and methods that can be applied to the study of the dynamics of various complex nonlinear dynamic economic systems. According to the author, the developed classification can significantly reduce the dimension of the set of options for choosing mathematical models and methods for describing and studying a complex nonlinear dynamic economic system, become the basis for creating a bank of models and has the potential to be useful for development of macroeconomic policy measures. In turn, the use of model bases by decision makers is devoted to result in an increase in the adequacy level of applied models of the research object, a rise in the reliability of forecasts and, finally, an improvement in management efficiency and a decrease in losses from making inappropriate management decisions.
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