Predicting the impact of e-commerce indices on international trade in Iran and other selected members of the Organization for Economic Co-operation and Development (OECD) by using the artificial intelligence and P-VAR model

Soheila Khajoui, Saeid Dehyadegari and Sayyed Abdolmajid Jalaee

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Abstract: This study aims at predicting the impact of e-commerce indicators on international trade of the selected OECD countries and Iran, by using the artificial intelligence approach and P-VAR. According to the nature of export, import, GDP, and ICT functions, and the characteristics of nonlinearity, this analysis is performed by using the MPL neural network. The export, import, GDP, and ICT findings were examined with 99 percent accuracy. Using the P-VAR model in the Eviews software, the initial database and predicted data were applied to estimate the impact of e-commerce on international trade. The findings from analyzing the data show that there is a bilateral correlation between e-commerce which means that ICT and international trade affect each other and the Goodness of fit of the studied model is confirmed.

Date: 2024-03
New Economics Papers: this item is included in nep-ara, nep-big, nep-ict and nep-int
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