Mathematical Models for Calculating the Development Dynamics in the Era of Digital Economy

Akaev, Askar; Садовничий, В. А.

doi:10.1134/s106456241806011x

Cited by 10 publications

(11 citation statements)

References 6 publications

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“…Comparing it with the trajectory of actual employment growth during the 5 th Kondratiev LW (1982-2018) (see Figure 3), it is clear that during the rise of the digital economy (2018-2040), workplaces will practically be stagnant. The trajectory of employment with balanced economic growth L 2 , calculated using Formula (14) and built on the same Figure 3, also supports the conclusion about the significant technological replacement of workplaces in the digital economy [29].…”

Section: Forecast Models For Calculating Potential Workplaces In Digisupporting

confidence: 63%

“…However, in the future digital economy, technological progress will already be determined by the dynamics of the production of technological information. That is why an information formula will be required to determine technological progress, which we obtained in the work [14] and verified for the information age (1980-2018). The mathematical models of economic dynamics and technological progress that are most suitable for the age of the digital economy are given below [25].…”

Section: Forecasting the Trajectory Of Economic Growthmentioning

confidence: 82%

“…To describe a long-term economic dynamics in a technologically developed country we can successfully use a classical Cobb-Douglas production function (PF) with a labour-saving technological (technical) progress [14]:…”

Section: Mathematical Models For Describing and Forecasting The Dynammentioning

confidence: 99%

“…In what follows we give an account of mathematical models for calculating and forecasting the dynamics of technological progress in information and digital economy, based on (speed) rates of the production of technological information. These information models first appeared in our work [14] and were developed in the work [25]. For practical application it is better to write and use PF (1) in a tempo-based form by means of its logarithmic differentiation:…”

Section: Mathematical Models For Describing and Forecasting The Dynammentioning

confidence: 99%

“…As can be seen from the brief review of the above-stated studies, many problematic issues of digital economy formation have already been investigated and quite interesting results, which answer these questions, have been obtained. In our work, we aimed to supplement and expand the existing methods of studying the digital economy, in particular on the basis of the information model developed by us [14], which allows us to predict technological progress on a longterm basis, using the growth rate of endogenous technological information in the economy. The article presents the main modes of production of technological information corresponding to the epochs of informatization and digitalization of the economy, as well as the Lagrangians that generate them.…”

Section: Introductionmentioning

confidence: 99%

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Information Models for Forecasting Nonlinear Economic Dynamics in the Digital Era

Akaev¹,

Sadovnichiy²

2021

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The aim of this study was to develop an adequate mathematical model for long-term forecasting of technological progress and economic growth in the digital age (2020-2050). In addition, the task was to develop a model for forecast calculations of labor productivity in the symbiosis of "man + intelligent machine", where an intelligent machine (IM) is understood as a computer or robot equipped with elements of artificial intelligence (AI), as well as in the digital economy as a whole. In the course of the study, it was shown that in order to implement its goals the Schumpeter-Kondratiev innovation and cycle theory on forming long waves (LW) of economic development influenced by a powerful cluster of economic technologies engendered by industrial revolutions is most appropriate for a long-term forecasting of technological progress and economic growth. The Solow neoclassical model of economic growth, synchronized with LW, gives the opportunity to forecast economic dynamics of technologically advanced countries with a greater precision up to 30 years, the time which correlates with the continuation of LW. In the information and digital age, the key role among the main factors of growth (capital, labour and technological progress) is played by the latter. The authors have developed an information model which allows for forecasting technological progress basing on growth rates of endogenous technological information in economics. The main regimes of producing technological information, corresponding to the eras of information and digital economies, are given in the article, as well as the Lagrangians that engender them. The model is verified on the example of the 5 th information LW for the US economy (1982-2018) and it has had highly accurate approximation for both technological progress and economic growth. A number of new results were obtained using the developed information models for forecasting technological progress. The forecasting trajectory of economic growth of developed countries (on the example of the USA) on the upward stage of the 6 th LW (2018-2042), engendered by the digital technologies of the 4 th Industrial Revolution is given. It is also dem-How to cite this paper: Akaev, A. and Sadovnichiy, V. (2021) Information Models for Forecasting Nonlinear Economic Dynamics in the Digital Era. Applied Mathematics, 12, 171-208.

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Section: Forecast Models For Calculating Potential Workplaces In Digisupporting

confidence: 63%

Section: Forecasting the Trajectory Of Economic Growthmentioning

confidence: 82%

Section: Mathematical Models For Describing and Forecasting The Dynammentioning

confidence: 99%

Section: Mathematical Models For Describing and Forecasting The Dynammentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Information Models for Forecasting Nonlinear Economic Dynamics in the Digital Era

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Sadovnichiy²

2021

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Digital Transformation and Growth Models

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Mathematical Models for Calculating the Development Dynamics in the Era of Digital Economy

Cited by 10 publications

References 6 publications

Information Models for Forecasting Nonlinear Economic Dynamics in the Digital Era

Information Models for Forecasting Nonlinear Economic Dynamics in the Digital Era

Revisited Economic Theory or How to Describe the Processes of Disequilibrium and Instability of Modern Economic Systems

Digital Transformation and Growth Models

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