Advances in Economics, Management and Political Sciences
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Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
Series Vol. 65 , 28 December 2023
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Analyze the Determinants of the Gini Index in the United States: An Econometrics Approach
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Abstract
Inequality has always been a topic of discussion among scholars. In this essay, one crucial measure of inequality—the Gini Index—is analyzed to find the influencing factors within the labor market. By running four regressions independently, the labor force changed from being positively related to being inversely correlated, and employment in services changed from being negatively associated to being positively related. The empirical results proved that the labor force, employment in agriculture as a percent of total employment, and unemployment rate are negatively related to the Gini index, and the rest of the variables (employment in service as a percent of total employment and population with tertiary degree) have a positive correlation. More labor force, employment in agriculture, and unemployment rate are accompanied by less Gini index. Take education level as an example; those at the top have better access to education and skill development in economies with significant income inequality, making them more likely to engage in higher-paying service or knowledge-based industries. Meanwhile, those with lower incomes may have fewer opportunities for schooling and are more likely to work in low-wage agricultural or manual labor employment.
Keywords
Gini Index, Inequality, Econometrics, United States
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
- ISBN (Print)
- 978-1-83558-239-8
- ISBN (Online)
- 978-1-83558-240-4
- Published Date
- 28 December 2023
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/65/20231586
- Copyright
- 28 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited