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A system dynamics model on the reasons of car price shocks after economic sanctions

Published: 06 December 2015 Publication History

Abstract

International Community can decide to establish several types of sanctions on the economy of a country. No matter the reasons of these sanctions, generally, they can have many adverse effects on the economy of the sanctioned country. This depends on the variety and extent of the sanctions. We propose a system dynamics model to capture some of the main reasons behind the economic instability in a sanctioned country. We consider a case study of the car price shocks occurred in Iran after the various economic sanctions that was established on 2012. Iran's economy depends heavily on the oil production and in fact, their main exports consist of the crude oil products. In our model, we combine causal loops for prediction of oil price after sanctions with those on predicting the car price. Our simulation results are consistent with the real data of the most common car's price in Iran.

References

[1]
Rafieisakhaei, M., B. Barazandeh, M. Bolursaz, and M. Assadzadeh. 2015, Jul. "Modeling Dynamics of Expectations on Global Oil Price". In The 33rd International Conference of the System Dynamics Society. MA, US.
[2]
Rafieisakhaei, M., and M. Jabbari. 2012, Jul. "Modeling the Impacts of Middle East and North Africa Unrest on the Global Oil Price". In The 30th International Conference of the System Dynamics Society. St. Gallen, Switzerland.
[3]
Sterman, J. D. 2000. Business dynamics: systems thinking and modeling for a complex world, Volume 19. Irwin/McGraw-Hill Boston.
  1. A system dynamics model on the reasons of car price shocks after economic sanctions

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    WSC '15: Proceedings of the 2015 Winter Simulation Conference
    December 2015
    4051 pages
    ISBN:9781467397414

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    Published: 06 December 2015

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    WSC '15: Winter Simulation Conference
    December 6 - 9, 2015
    California, Huntington Beach

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    WSC '15 Paper Acceptance Rate 202 of 296 submissions, 68%;
    Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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