Forecasting Foreign Direct Investment Inflow to Egypt and Determinates: Using Machine Learning Algorithms and ARIMA Model

• Main Authors: Abd El-Aal, M.F (Author), Abdul Rahman, R. (Author), Algarni, A. (Author), Alrashidi, K. (Author), Fayomi, A. (Author)
• Format: Article
• Language: English
• Published: Hindawi Limited 2021
• Series: Journal of Advanced Transportation
• Subjects: Accurate prediction; Adaptive boosting; Algorithm model; ARIMA models; 'current; Economic indicators; Economics; Foreign direct investments; Gradient boosting; Gross domestic products; Human development index; Machine learning; Machine learning algorithms; Population statistics
• Online Access: View Fulltext in Publisher; View in Scopus

 This study aims to determine the primary determination of FDI inflow to Egypt using machine learning algorithms and the ARIMA model and get an accurate prediction of FDI inflow to Egypt during the current decade (2020-2030) and approved that the gradient boosting model is the most accurate algorithms. Also, we find stability in economic indicators in Egypt during the current decade using the ARIMA model. The last step approved that the primary determinant of FDI inflow to Egypt is the Human Development Index, followed by population size, gross domestic product per capita, lending rate, and gross domestic product value. © 2021 Mohamed F. Abd El-Aal et al.