The Impact Factors of Gini Coefficient: Taking the US as an Example

Abstract

The study aims to explore multiple variables affecting the Gini coefficient in the United States, including economic expansion, governmental measures, urban development, quality of life, and global trade. The research methodology involves using publicly accessible data from the official online portal of the United Nations, covering a wide array of economic, societal, and regulatory parameters. Through regression analysis, the study delves into the relationship between variables such as GDP, urbanization, living standards, global trade, and net migration with the Gini coefficient. The purpose is to gain a profound understanding of the determinants influencing the Gini coefficient in the United States. The study reveals that the relationship between net migration and the Gini coefficient is not significant, implying that changes in the Gini coefficient in the United States are not notably influenced by net migration. Additionally, changes in urban and rural populations do not exert a noteworthy influence over the Gini coefficient. The significance of this research lies in its comprehensive approach, considering not just economic expansion and governmental measures but also new factors like urban development, quality of life, and global trade. Through regression analysis, the study offers a new perspective on the multiple factors affecting the Gini coefficient in the United States. Given that net migration and changes in urban and rural populations do not significantly impact the Gini coefficient, policymakers and leaders should consider other factors like economic expansion, governmental measures, quality of life, and global trade to effectively influence the Gini coefficient and reduce income inequality.