GDP growth drivers in Saudi Arabia based on machine learning algorithms

被引:0
|
作者
Abd El-Aal, Mohamed F. [1 ]
Shrahili, Mansour [2 ]
Kayid, Mohamed [2 ]
Mohammad, Shahid [3 ]
机构
[1] Arish Univ, Fac Commerce, Econ Dept, Arish, North Sinai, Egypt
[2] King Saud Univ, Coll Sci, Dept Stat & Operat Res, POB 2455, Riyadh 11451, Saudi Arabia
[3] Univ Wisconsin, Oshkosh, WI 54901 USA
关键词
ECONOMIC-GROWTH; CONSUMPTION; INVESTMENT;
D O I
10.1016/j.jrras.2025.101380
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This study utilizes machine-learning algorithms to investigate the economic sectors that most significantly influence Saudi Arabia's economic growth rate, focusing on agriculture, industry, and services. The analysis shows that the random forest algorithm offers the highest predictive accuracy in identifying the key sectors driving economic growth. The research findings show that the service and industrial sectors account for 39.3% and 37.7% of Saudi Arabia's GDP growth, respectively. These results show that this country is moving significantly toward diversifying its economy as it depends more and more on non-oil sectors for growth. Even while the agricultural industry presently makes up a lower 23% of the total GDP, its comparison small share does not limit its potential for expansion. The paper emphasizes how agricultural developments, such as enhanced technologies and more efficient methods, could increase economic impact. The agricultural sector has the potential to play a significant role in boosting future economic growth, which would further help Saudi Arabia's objectives for sustainable growth and diversification.
引用
收藏
页数:8
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