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Long-term Macroeconomic Dynamics of Competition in the Russian Economy using Agent- based Modelling

Long-term Macroeconomic Dynamics of Competition in the Russian Economy using Agent- based Modelling

Tatyana Eftonova (Ufa State Aviation Technical University, Ufa, Russia), Mariam Kiran (School of Electrical Engineering and Computer Science, University of Bradford, Bradford, UK), and Mike Stannett (Department of Computer Science, University of Sheffield, Sheffield, UK)
Copyright: © 2017 |Volume: 6 |Issue: 1 |Pages: 20
ISSN: 2160-9772|EISSN: 2160-9799|EISBN13: 9781522515296|DOI: 10.4018/IJSDA.2017010101
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MLA

Eftonova, Tatyana, et al. "Long-term Macroeconomic Dynamics of Competition in the Russian Economy using Agent- based Modelling." IJSDA vol.6, no.1 2017: pp.1-20. https://doi.org/10.4018/IJSDA.2017010101

APA

Eftonova, T., Kiran, M., & Stannett, M. (2017). Long-term Macroeconomic Dynamics of Competition in the Russian Economy using Agent- based Modelling. International Journal of System Dynamics Applications (IJSDA), 6(1), 1-20. https://doi.org/10.4018/IJSDA.2017010101

Chicago

Eftonova, Tatyana, Mariam Kiran, and Mike Stannett. "Long-term Macroeconomic Dynamics of Competition in the Russian Economy using Agent- based Modelling," International Journal of System Dynamics Applications (IJSDA) 6, no.1: 1-20. https://doi.org/10.4018/IJSDA.2017010101

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Abstract

Agent-based economic modelling techniques are increasingly being used to complement standard economic simulations. This paper re-models a standard equation-based simulation model of the Russian macroeconomy in an agent-based setup, and uses it to investigate the effect that antimonopoly legislation can be expected to have upon long-term dynamic behaviour. The results reveal various potential outcomes which would have not been visible using traditional equation-based modelling techniques. While the number of economic agents has been kept deliberately small in the work presented here, the modelling approach is scalable to systems incorporating many millions of agents.

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