A Statistical Model for Analyzing the Impact of GDP Components on the Manufacturing Sector in Saudi Arabia

  • Bader Alanazi Department of Mathematics, College of Science, Northern Border University, Arar 73222, Saudi Arabia,
DOI: https://doi.org/10.19139/soic-2310-5070-2261
Keywords: Regression analysis, Statistical Model, Regression Assumptions, Economic Sectors, Model Accuracy.

Abstract

This study examines the relationship between the Gross Domestic Product (GDP) of the manufacturing sector and various independent sectors in Saudi Arabia, utilizing a comprehensive dataset from 2010 to 2023 sourced from the General Authority for Statistics. A robust statistical model was developed to analyze these relationships, revealing significant insights into how changes in different sectors influence manufacturing GDP. Our findings indicate that increases in GDP from specific sectors, such as mining and construction, lead to growth in manufacturing GDP, while increases in other sectors, such as transport and community services, may negatively impact manufacturing performance. These insights are vital for policymakers, emphasizing the interconnectedness of economic sectors and the need for coordinated strategies. This research not only contributes to a deeper understanding of the dynamics shaping Saudi Arabia’s economic landscape but also provides a valuable foundation for future studies and policy interventions aimed at strengthening the manufacturing sector and promoting sustainable economic development.
Published
2024-12-19
How to Cite
Alanazi, B. (2024). A Statistical Model for Analyzing the Impact of GDP Components on the Manufacturing Sector in Saudi Arabia. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-2261
Issue
Online First
Section
Research Articles
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