Using Fuzzy Logic Method to Investigate the Effect of Economic Sanctions on Business Cycles in the Islamic Republic of Iran

One of the main economic issues in Iran is the issue of economic sanctions. These sanctions have been imposed by various institutions and countries around the world in various forms since 1979 against Iran. Economic sanctions have affected large sections of Iran’s economy. Meanwhile, economic sancti...

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Bibliographic Details
Published in:Applied computational intelligence and soft computing Vol. 2021; pp. 1 - 10
Main Authors: Saeed Iranmanesh, M. I., Norallah Salehi, A., Seyyed Abdolmajid Jalaee, B.
Format: Journal Article
Language:English
Published: New York Hindawi 2021
Hindawi Limited
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Summary:One of the main economic issues in Iran is the issue of economic sanctions. These sanctions have been imposed by various institutions and countries around the world in various forms since 1979 against Iran. Economic sanctions have affected large sections of Iran’s economy. Meanwhile, economic sanctions against Iran have had far-reaching effects on trade cycles in Iran. The purpose of this article is to investigate the impact of economic sanctions on the structure of business cycles in Iran. The sanction index is a tool for studying quantitative sanctions. The opinions of 15 experts in sanctions economics were collected using fuzzy questionnaires. And the sanction index was obtained. The fuzzy logic method in the MATLAB software space calculated the economic sanction index for 1979–2019. The self-regression calculated the effect of economic sanctions on business cycles. There are two scenarios in this article. In scenario 1, sanctions increased inflation, reduced production, and reduced investment. Also, during the embargo period, the recessions are longer. The second scenario of the research shows the economy without sanctions. The results showed that, in these conditions, inflation has less effect on production and investment. And the economy will experience a long period of prosperity without sanctions.
ISSN:1687-9724
1687-9732
DOI:10.1155/2021/8833474