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

IF 2.5 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Journal of Radiation Research and Applied Sciences Pub Date : 2025-02-09 DOI:10.1016/j.jrras.2025.101342
Mohamed F. Abd El-Aal , Mansour Shrahili , Mohamed Kayid , Oluwafemi Samson Balogun
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Abstract

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.
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埃及与金砖国家双边贸易的决定因素:基于传统计量经济学和机器学习算法的引力模型
本文采用经典计量经济学技术和机器学习方法,特别是泊松-牛顿-拉夫森、梯度增强(GB)和随机森林(RF),探讨影响埃及与金砖国家双边贸易的因素。设计/方法/本研究利用传统的计量经济学分析(泊松-牛顿-拉夫森)来探讨贸易量与各因素之间的相关性。机器学习算法(GB和RF)也对影响因变量(交易量)的重要自变量进行排名。该研究利用了多种因素,包括人口规模、产业增加值、人均GDP、固定资本形成总额、地理距离、GDP增长和全球GDP扩张。泊松-牛顿-拉夫森分析显示,贸易量与几个因素呈负相关,包括人口规模、工业增加值、金砖国家人均GDP、埃及固定资本形成总额和地理距离。相反,埃及的人均GDP、工业增加值、金砖国家固定资本形成总额、GDP增长和全球总体GDP扩张之间存在正相关关系。该分析还强调了机器学习结果中最重要的因素,确定了金砖国家GDP规模、全球GDP规模以及国家之间的距离是最重要的影响因素。研究启示研究结果强调了基本引力模型中基本变量的重要性,强调了全球GDP规模作为第二大影响因素的关键作用。此外,该研究强调了生产部门在塑造当地产出方面的重要性,为贸易关系的竞争性或互补性提供了见解。这些影响有助于全面理解影响埃及和金砖国家之间贸易流动的多方面决定因素。
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来源期刊
自引率
5.90%
发文量
130
审稿时长
16 weeks
期刊介绍: Journal of Radiation Research and Applied Sciences provides a high quality medium for the publication of substantial, original and scientific and technological papers on the development and applications of nuclear, radiation and isotopes in biology, medicine, drugs, biochemistry, microbiology, agriculture, entomology, food technology, chemistry, physics, solid states, engineering, environmental and applied sciences.
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