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Computer Research and Modeling, 2021, Volume 13, Issue 4, Pages 859–873
DOI: https://doi.org/10.20537/2076-7633-2021-13-4-859-873
(Mi crm921)
 

This article is cited in 4 scientific papers (total in 4 papers)

MODELS OF ECONOMIC AND SOCIAL SYSTEMS

Modernization as a global process: the experience of mathematical modeling

S. Yu. Malkova, O. I. Davydovab

a Center for Long-Term Forecasting and strategic planning of Moscow State University, 1 Leninskie gory st., Moscow, 119991, Russia
b iDeсide Consulting LLC, office 32, 6b Kalinina st., Korolev, 141070, Russia
References:
Abstract: The article analyzes empirical data on the long-term demographic and economic dynamics of the countries of the world for the period from the beginning of the 19th century to the present. Population and GDP of a number of countries of the world for the period 1500–2016 were selected as indicators characterizing the long-term demographic and economic dynamics of the countries of the world. Countries were chosen in such a way that they included representatives with different levels of development (developed and developing countries), as well as countries from different regions of the world (North America, South America, Europe, Asia, Africa). A specially developed mathematical model was used for modeling and data processing. The presented model is an autonomous system of differential equations that describes the processes of socio-economic modernization, including the process of transition from an agrarian society to an industrial and post-industrial one. The model contains the idea that the process of modernization begins with the emergence of an innovative sector in a traditional society, developing on the basis of new technologies. The population is gradually moving from the traditional sector to the innovation sector. Modernization is completed when most of the population moves to the innovation sector.
Statistical methods of data processing and Big Data methods, including hierarchical clustering were used. Using the developed algorithm based on the random descent method, the parameters of the model were identified and verified on the basis of empirical series, and the model was tested using statistical data reflecting the changes observed in developed and developing countries during the period of modernization taking place over the past centuries. Testing the model has demonstrated its high quality — the deviations of the calculated curves from statistical data are usually small and occur during periods of wars and economic crises. Thus, the analysis of statistical data on the long-term demographic and economic dynamics of the countries of the world made it possible to determine general patterns and formalize them in the form of a mathematical model. The model will be used to forecast demographic and economic dynamics in different countries of the world.
Keywords: modernization, countries of the world, long-term demographic and economic dynamics, mathematical modeling.
Funding agency Grant number
Russian Science Foundation 20-61-46004
The work was carried out within the framework of the Program for the Development of the Interdisciplinary Scientific and Educational School of Moscow University «Mathematical Methods for the Analysis of Complex Systems» with the support of the Russian Science Foundation (project No. 20-61-46004).
Received: 15.02.2021
Revised: 23.06.2021
Accepted: 30.06.2021
Document Type: Article
UDC: 51-77
Language: Russian
Citation: S. Yu. Malkov, O. I. Davydova, “Modernization as a global process: the experience of mathematical modeling”, Computer Research and Modeling, 13:4 (2021), 859–873
Citation in format AMSBIB
\Bibitem{MalDav21}
\by S.~Yu.~Malkov, O.~I.~Davydova
\paper Modernization as a global process: the experience of mathematical modeling
\jour Computer Research and Modeling
\yr 2021
\vol 13
\issue 4
\pages 859--873
\mathnet{http://mi.mathnet.ru/crm921}
\crossref{https://doi.org/10.20537/2076-7633-2021-13-4-859-873}
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  • https://www.mathnet.ru/eng/crm/v13/i4/p859
  • This publication is cited in the following 4 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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