Using Artificial Intelligence Algorithms to Study the Relative Importance of Macroeconomic Variables on Foreign Trade in Iraq
DOI:
https://doi.org/10.25195/ijci.v50i2.504Keywords:
Artificial Neural Networks; Macroeconomic Variables; Gross Domestic Product; Foreign Direct Investment; Descriptive Analytical ApproachAbstract
International trade is considered the central link in the complex system of contemporary international economic relations. It links all countries of the world in a unified economic system whose goal is to address economic problems at the international level through developing productive capacity, expanding employment opportunities, and enhancing the flow of production factors between countries to achieve economic growth. Our study aimed to clarify the considerable impact of some macroeconomic variables (exchange rate, gross domestic product, public spending, foreign direct investment) on foreign trade in Iraq and to determine the degree of relative importance of the macroeconomic variables affecting foreign trade in Iraq. The study followed the descriptive analytical approach by collecting data related to the study for the period from 2003 to 2020 and then analyzing the data obtained through artificial neural networks.
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