Determinants of bilateral trade between Egypt and BRICS: Gravity model with traditional econometrics and machine learning algorithms

Purpose

This paper explores the factors influencing bilateral trade between Egypt and BRICS by employing classic econometric techniques and machine learning methods, specifically Poisson Newton-Raphson, gradient boosting (GB), and random forest (RF).

Design/methodology/

The investigation utilizes traditional econometric analysis (Poisson Newton-Raphson) to explore the correlation between trade volume and various factors. Machine learning algorithms (GB and RF) also rank significant independent variables affecting the dependent variable (trade volume). The study leverages diverse factors, including population size, industry value added, GDP per capita, gross fixed capital formation, geographical distance, GDP growth, and global GDP expansion.

Findings

The Poisson Newton-Raphson analysis shows an inverse correlation between trade volume and several factors, including the population size, industry value added, GDP per capita of BRICS nations, Egypt's gross fixed capital formation, and geographical distance. In contrast, positive correlations exist with Egypt's GDP per capita, industry value added, BRICS gross fixed capital formation, GDP growth, and overall global GDP expansion. The analysis also highlights the most significant factors in machine learning outcomes, identifying BRICS GDP size, global GDP size, and the distance between countries as the top influences.

Research implications

The findings underscore the significance of fundamental variables in the basic gravity model, emphasizing the crucial role of global GDP size as the second most influential contributor. Furthermore, the study highlights the importance of productive sectors in shaping local outputs, providing insights into trade relationships' competitive or complementary nature. These implications contribute to a comprehensive understanding of the multifaceted determinants shaping trade flows between Egypt and BRICS nations.