Nowcasting Egypt GDP Using machine learning Algorithms

AbdElminaam, Diaa S; Abd El-Aal, Mohamed; Abdellatif, Alaa

doi:10.21608/jocc.2023.282073

Nowcasting Egypt GDP Using machine learning Algorithms

Document Type : Original Article

Authors

¹ Department of Data Science , Faculty of Computer Science , Misr International University , Cairo , Egypt

² Economics, faculty of commerce, Arish University

³ higher Institute of Commercial Sciences, Mahla, Egypt

10.21608/jocc.2023.282073

Abstract

This paper aims to determine the most accurate algorithm for predicting the Egyptian gross domestic product (GDP) and not only and also to determine the relative weight of the effect of the components of the output on it to assist decision-makers in making good economic policies. It turned out that the gradient algorithm is the most accurate and highly efficient algorithm for predicting the Egyptian GDP. It also became clear that government investment is the biggest
influence on the Egyptian GDP at 21%, followed by the consumer spending of the family sector at 19%, followed by investment spending by the private sector and imports by the same 15%, then exports and government spending by 14% and 13%, respectively. Thus, to stimulate and maximize the size of the Egyptian GDP, the decision-maker must focus on stimulating government investment spending and consumer spending for the household sector and investment spending for the private sector.

Keywords