Synergetic approach to macroeconomic studies

This paper confirms the principal possibility of using synergetics in macroeconomic studies. It noted that the presence in economic systems of all science typologies requires using subjects of natural and engineering sciences for the study of economic objects as well. Ignoring this fact hinders the development of fundamental economic knowledge and, as consequence, conditions the use of metaphysical concepts in developed models. Since the above interdisciplinarity is inherent in synergetics, its applicability in macroeconomics is considered. On the example of modeling economic systems, it is demonstrated that their essence (nonlinear space-time structure) corresponds to the basic provisions of synergetics. Therefore, its tools are eligible in the tasks of macroeconomic analysis. As an example, this paper proposes the stochastic model of economic cycles explaining their phenomenon as well as providing the quantitative (parametric) description of cycles. Novelty of the model describing the cycles as random oscillations is tied to the probabilistic description of the investment function and the perception of the economic system as a material object with certain inherent properties. According to a proposed model, the income oscillations are induced by both exogenous (investment fluctuations) and endogenous (economic system elasticity) causes. The values of fluctuations of the income function around its longterm trend relate to the value of intensity of investment fluctuations as well as the gain (efficiency) of the economic system. The duration of the cycle is related to the inclusive wealth of the system and its dynamic factor, which characterizes the system’s ability to withstand investment fluctuations as well as to eliminate their consequences. Prospects of practical applications of the considered model were demonstrated on the example of cycle management.

Keywords

object of science, subject of science, synergetics, economic system, investment function, income function, economic cycles, random oscillations

Publication date

13.12.2021

Number of characters

22709

Cite

GOST	Karmalita V. Synergetic approach to macroeconomic studies // Ekonomika i matematicheskie metody – 2021. – V. 57. – Issue 4 C. 17-26 [Electronic resource]. URL: https://emm.jes.su/S042473880017525-6-1 (circulation date: 07.10.2024). DOI: 10.31857/S042473880017525-6
MLA	Karmalita, Viacheslav A "Synergetic approach to macroeconomic studies." Ekonomika i matematicheskie metody 57.4 (2021):17-26. DOI: 10.31857/S042473880017525-6
APA	Karmalita V. (2021). Synergetic approach to macroeconomic studies. Ekonomika i matematicheskie metody 57(4), pp.17-26 DOI: 10.31857/S042473880017525-6

100 rub.

When subscribing to an article or issue, the user can download PDF, evaluate the publication or contact the author. Need to register.

Number of purchasers: 0, views: 490

Readers community rating: votes 0

1. 30 Years of synergetics (2000). Interview with Professor Hermann Haken. Voprosy Filosofii, 3, 53–61 (in Russian).
2. Ashby W.R. (1962). Principles of the self-organizing system. In: H. Foerster von, G. Zopf (Eds.). Principles of self-organization. London: Pergamon Press, 255–278.
3. Bogolubov N.N., Mitropol'skii Yu.A. (1974). Asymptotic methods in theory of nonlinear oscillations. Moscow: Nauka. 504 p. (in Russian).
4. Bolotin V.V. (2010). Random vibrations of elastic systems. Berlin: Springer Verlag. 468 p. Translated from the Russian. (Originally published by Moscow: Nauka, 1979).
5. Denisova L.B. (2012). Systematics of knowledge and classification models of sciences. Scientific Bulletin of the Omsk Academy of the Internal Affairs Ministry of Russia, 1 (44), 60–64 (in Russian).
6. Essays on economic synergetics (2017). V.I. Mayevsky, S.G. Kirdina-Chandler, M.A. Deryabina (Eds.). Moscow: Institute of Economics, Russian Academy of Sciences. 182 p. (in Russian).
7. Haken H. (1980). Synergetics. Translated from the English. Moscow: Mir. 404 p. (in Russian).
8. Karmalita V. (2020). Stochastic Dynamics of Economic Cycles. Berlin, Boston: De Gruyter, 106 p.
9. Karmalita V.А. (2019). Digital processing of random oscillations. Berlin, Boston: De Gruyter. 95 p.
10. Korotaev A.V., Tsirel S.V. (2010). Spectral analysis of world GDP dynamics: Kondratieff waves, Kuznets swings, Juglar, and Kitchin cycles in global economic development, and the 2008–2009 economic crisis. Structure and Dynamics, 4 (1), 1–56.
11. Kuznetsov Yu. A. (2011). Mathematical Modeling of Economic Cycles: Facts, Concepts, Results. // Economic Analysis: Theory and Practice, 8 (225), 42–56 (in Russian).
12. Kvon D.Kh. (2020). The constant number one of all Nature // Nezavisimaya Gazeta, 269 (in Russian).
13. Polansky S., Bryant B., Hawthorne P., Johnson J., Keeler B., Pennington D. (2015). Inclusive wealth as a metric of sustainable development. Ann. Rev. of Environment and Resource, 40, 445–466.
14. Samuelson P., Nordhaus W. (2005). Economics. Moscow: Vil'jams. Translated from the English (Originally published by McGraw-Hill: Irwin, 18th ed., 2004. 800 p.) (in Russian).
15. Willems J.C. (1972). Dissipative dynamic systems. Part I: General theory. Archive for Rational Mechanics and Analysis, 45, 321–352.
16. Zhang W.-B. (1999). Synergetic Economics: Time and Change in Nonlinear Economics. Translated from the English by Berlin, Heidelberg: Springer Verlag. 361 p. (in Russian).
17. Zhulanov A.L. (2013). Towards the relationship between the concepts of the object and the subject of science in classical and non-classical natural science. Bulletin of Perm State Humanitarian Pedagogical University (PSHPU). Series 3. Humanities and Social Sciences, 1, 17–26 (in Russian).