On a method of modeling of socio-economic processes dynamics

  • Natalia V. Loginova Saint Petersburg State University, Saint Petersburg, Russia
Keywords: dynamical systems, probability chains, statistical criteria, extrapolation, econometric analysis

Abstract

In economic science, researchers have been long studying the possibility of using mathematical apparatus to perform a complete and accurate analysis and build a reliable forecast of the studied economic processes. There is a large number of different ways to create mathematical models that allow the construction the dynamics of changes in socio-economic data. In this article, author applies two types of discrete probability chains, which are generalization of well known Markov processes, to the modeling of dynamics of two types of data. The initial data are checked by using several statistical criteria. The analysis of the consistency of results with empirical dynamics has been made. The results shows that the satisfaction of statistical criteria is important for successful application of discrete probabilistic chains.

Author Biography

Natalia V. Loginova, Saint Petersburg State University, Saint Petersburg, Russia

Graduate student, Computer Science Department SPbSU; 198504, Russia, St.Petersburg, Starii Petergof, Universitetski pr. 28, faculty of Mathematics and Mechanics SPbGU, computer science department., natalia.loginowa@gmail.com

References

Афанасьева Е. В. Моделирование процессов распределения ресурсов с помощью вероятностных цепочек // Дифференциальные уравнения и процессы управления. 2011. № 3. С. 84–137.

Афанасьева Е. В. Моделирование процессов потребления экономических ресурсов с помощью вероятностных цепочек (на примере стран Западной Европы) // Научно-технические ведомости СПбГПУ: Информатика. Телекоммуникации. Управление. СПб.: Политехн. ун-та. 2011. № 3. С. 93–97.

Магнус Я. Р., Катышев П. К., Пересецкий А. А. Эконометрика: начальный курс. Академия народного хозяйства (М.). 6-е изд., перераб. и доп. М. : Дело, 2009.

Носко В. П. Эконометрика: в 2 кн.: учебник для вузов. М.: Дело, 2011.

Вербик М. Путеводитель по современной эконометрике. М.: Научная книга, 2008.

Айвазян С. А., Иванова С. С. Эконометрика. М.: Маркет ДС, 2010.

Айвазян С. А., Мхитарян В. С. Прикладная статистика и основы эконометрики. М.: ЮНИТИ, 2008.

Елисеева И. И. Эконометрика. М.: Финансы и статистика, 2005.

Sonis M. Discrete Non-Linear Probabilistic Chains (M. Drachlin and E. Litsyn eds) // Functional Differential Equations, Ariel, Israel, 2003. № 10. Р. 445–487.

Sonis M., Azzoni C. R., Hewings G. J. D. The Three-sector Growth Hypothesis and the Euler-Malthus Economic growth model: Application to the analysis of GDP dynamics of Brazil, 1985–2004–2020 // The Fifth International Conference on Mathematical Modeling and Computer Simulation of Materials Technologies. 2008. P. 153–163.

Sonis M., Hewings G. Regional Competition and Complementarity: Comparative Advantages / Disadvantages and Increasing / Diminishing Returns in Discrete Relative Spatial Dynamics // Regional Competition Advances in Spatial Science / P. Batey, P. Friedrich. Berlin: SpringerVerlag, 2001. P. 139–157.

Федеральная служба государственной статистики [Online]. Available: http://www.gks.ru (дата обращения: 26.04.2018).

Allin Cottrell. Department of Economics, Wake Forest University. Riccardo "Jack"Lucchetti. Department of Economics, Marche Polytechnic University. Gretl User’s Guide. Gnu Regression, Econometrics and Time-series Library [Online]. Available: http://gretl.sourceforge.net/gretl-help/ gretl-guide.pdf (дата обращения: 6.04.2018).

Published
2018-04-27
How to Cite
Loginova, N. V. (2018). On a method of modeling of socio-economic processes dynamics. Computer Tools in Education, (2), 14-24. https://doi.org/10.32603/2071-2340-2018-2-14-24
Section
Algorithmic mathematics and mathematical modelling