Aggrerated Simulation Model of Foreigh Economic Activity of the Russian Federation
Abstract
This article presents the developed aggregated simulation model of foreign economic interaction of the Russian Federation with partner countries. The bi-criterion optimization problem of the rational control of foreign trade activities is formulated and solved with consideration of the differently directed interests of the Russian Federation and partner countries. The possibilities of such links to be balanced are being studied depending on different scenarios reflecting the foreign trade strategy characteristic for the respective groups of countries (EU, APEC, EEC, etc.). The proposed simulation model implemented in AnyLogic allowed investigating the influence of the key control parameters of foreign economic activity on the characteristics of the interrelationships of the Russian Federation with other countries. Suboptimal (scenario) values of import duties and quotas that provide the best influence on the forecast dynamics of the foreign trade turnover of the Russian Federation are calculated.
Keywords
Journal of Economic Literature (JEL): C02, C63
About the Author
Gayané L. BeklaryanRussian Federation
References
1. Akopov A.S. (2014). Simulation modeling. A textbook and a workshop for academic baccalaureate. Moscow, URAIT, 389 p. (in Russian).
2. Akopov A.S., Beklaryan G.L. (2005). Analysis of efficiency of adjusting policy of the state by means of regional model CGE of behavior of natural monopolies (on the example of electric power industry). Economics of Contemporary Russia, no. 4, pp. 123–129 (in Russian).
3. Akopov A.S., Beklaryan L. (2015). An agent model of crowd behavior in emergencies. Automation and Remote Control, no. 10, pp. 1817–1827.
4. Akopov A.S., Beklaryan A.L., Khachatryan N.K., Fomin A.V. (2018). Development of an adaptive genetic optimization algorithm using agent modeling methods. Information Technology, vol. 24, no. 5, pp. 321–329 (in Russian).
5. Akopov A.S., Khachatryan N.K. (2016). Agent-based modelling. A teaching guide. Moscow, CEMI RAS, 76 p. (in Russian).
6. Bakhtizin A.R. (2008). Agent-oriented models of economics. Moscow, Ekonomika, 279 p. (in Russian).
7. Golovanova S.V. (2009). International trade – the factor of the change in the concentration of production in the Russian industry (1998–2004). Economics of Contemporary Russia, vol. 1, no. 1, pp. 129–137 (in Russian).
8. Kovaleva O.A. (2009). Modeling the strategy of decisionmaking on customs and tariff regulation of foreign economic activity. Ekonomika Promyslennosti [Economics of Industry], vol. 44, no. 1, pp. 86–94 (in Russian).
9. Kylbaev E.S. (2016). Using gravity models to predict the foreign trade between countries. Voprosy Novoi Ekonomiki [Issues of the New Economy], no. 1 (37), pp. 29–34 (in Russian).
10. Makarov V.L., Bakhtizin A.R., Bakhtizina A.R. (2009). Computable model of the knowledge economy. Economics and Mathematical Methods, vol. 45, no. 1, pp. 70–82 (in Russian).
11. Makarov V.L., Bakhtizin A.R., Sulakshin S.S. (2007). Using computable models in public administration. Moscow, Scientific expert, 306 p. (in Russian).
12. Makarov V.L. (1999). Computable model of the Russian economy (RUSEC). Working paper # WP/99/069. Moscow, CEMI RAS, 93 (in Russian).
13. Uziakov M.N., Tkathenko A.V., Sapova N.N., Khersonsky A.A., Shirov A.A., Shoshkin S.P., Yantovsky A.A. (2004). Multilevel system of foreign trade forecasting models construction problems in transition economy. Scientific Articles: Institute of Economic Forecasting (RAS), no. 2, pp. 10–23 (in Russian).
14. Forrester J.W. (1961). Industrial dynamics. MIT Press.
15. Zitzler E., Thiele L. (1999). Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Transactions on Evolutionary Computation, no. 3 (4), pp. 257–271.
Review
For citations:
Beklaryan G.L. Aggrerated Simulation Model of Foreigh Economic Activity of the Russian Federation. Economics of Contemporary Russia. 2018;(4):50-65. (In Russ.)