Agent-Based Modeling of Global Agro-Food Market

Abstract 
With the turbulence in global trade and the necessity to develop non-commodity exports in Russia, the choice of an effective strategy for exporters’ conduct in the food market is becoming vitally important these days. Agent-based models simulating the behavior of decentralized self-learning agents with their own goals and capabilities can be used as the tools for analyzing and predicting market movements. The paper presents the results of the agent-based approach to market modeling by the example of barley, which is one of the top commodity items of the Russian food exports on 
the basis of FAOSTAT and Rosstat data for the period 1997–2017. As a result of the study, an agent-based model of the world barley market was built, and a series of calculated experiments was carried out in the AnyLogic development environment with the changes in such factors as the level of global demand, the amount of customs duties, the exporting companies’ funds in order to determine the strategic conduct of the exporting agents taking into account the limited rationality of the participants in communicative interaction. The proposed approach develops modern theory of consumer behavior and simulation, and the results of the study can be used in the formation of development programs 
for the Russian agro-food exports. 

Keywords 
agent-based modeling, export market, simulation modeling, market demand, consumer behavior 

Funding 
The publication is prepared within the project No. XI.171.1.1 “Development of program complexes and information systems for analysis and forecast of socio-economic process, their testing and implementation in theoretical and applied research”, no. АААА-А17-117022250129-2 according to the research plan of the IEIE SB RAS 

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References:

1. Weiping Wang, Saini Yang, Fuyu Hu, Zhangang Han, Carlo Jaeger. An agent-based modeling for housing prices with bounded rationality. IOP Conf. Series: Journal of Physics: Conf. Series 1113. 2018. № 012014. DOI 10.1088/1742-6596/1113/1/012014 
2. Hamill L., Gilbert N. Agent-Based Modelling in Economics. UK. Wiley, 2015, 246 p. 
3. Bakhtizin A. R. Agent-orientirovannye modeli ekonomiki [Agent-oriented models of the economy]. Moscow, Ekonomika. 2008, 279 p. (in Russ.) 
4. Okrepilov V. V., Makarov V. L., Bakhtizin A. R., Kuzmina S. N. Application of Supercomputer Technologies for Simulation of Socio-Economic Systems. Economy of region, 2015, no. 2, p. 301–313. (in Russ.) 
5. Suslov V. I., Domozhirov D. A., Kostin V. S., Melnikova L. V., Ibragimov N. M., Tsyplakov A. A. Agent-based Modeling of Spatial Processes in World Economy. Region: Economics and Sociology, 2014, no. 4, p. 32–54. (in Russ.) 
6. Deissenberg C., Hoog S. van der, Herbert D. EURACE: A Massively Parallel Agent-Based Model of the European Economy. Applied Mathematics and Computation, 2008, vol. 204 (2), p. 541–552. DOI 10.1016/j.amc.2008.05.116 
7. Otmakhova Yu. S., Efremov D. V. Podkhody k razrabotke arkhitektury agentnoy sistemy.  In: Ekonomicheskoe razvitie Rossii: regional'nyy i otraslevoy aspekty: sb. nauch. tr. Eds.  E. A. Kolomak, L. V. Mashkina; IEIE SBRAS. Novosibirsk, 2014, iss. 13, p. 126–139. (in Russ.) 
8. Usenko N. I., Poznyakovsky V. M., Otmakhova Yu. S. “Palm Oil Paradise” or “Palm Oil Octopus”? Current Trends and Threats of Food Markets. EKO [ECO], 2014, no. 9, p. 135–152. (in Russ.) 
9. Usenko N. I., Otmakhova Yu. S., Olovyanishnikov A. G. The issues of asymmetry of corporate and public interests in the food market. Economic and social changes: facts, trends, forecast, 2014, no. 3, p. 124–139.   
10. Abdou M., Hamill L., Gilbert N. Designing and building an agent-based model. In: Agent-Based Models of Geographical Systems. Springer, 2012, p. 141–165. DOI 10.1007/978-90-481-8927-4 
11. Makarov V. L., Bakhtizin A. R., Sushko E. D., Vasenin V. A., Borisov V. A., Roganov V. A. Supercomputer technologies in social sciences: Agent-oriented demographic models. Herald of the Russian Academy of Sciences, 2016, vol. 86, no. 3, p. 248–257.