STATISTICAL ANALYSIS OF INCOME INEQUALITY AND POVERTY INDICATORS
Keywords:
Income Inequality, Poverty Indicators, Gini Coefficient, Theil Index, Palma Ratio, Poverty Headcount, Statistical Analysis, Econometrics, Regression, Decomposition, Inclusive Growth, Social Policy.Abstract
Income inequality and poverty remain central issues in global economic development, particularly in emerging economies where rapid growth is often accompanied by uneven distribution of wealth. This paper presents a comprehensive statistical analysis of income inequality and poverty indicators, focusing on both their measurement and interrelationship. Utilizing cross-sectional and time-series data, key indices such as the Gini coefficient, Theil index, Palma ratio, and poverty headcount ratio are examined to assess inequality dynamics. The study applies econometric modeling, including regression analysis and panel data techniques, to identify the main socioeconomic and policy-driven determinants influencing inequality and poverty levels. Additionally, decomposition methods are used to explore the contribution of education, employment, demographic changes, and social policies to income disparities. The findings highlight the complexity of the inequality-poverty nexus and underscore the importance of targeted policy interventions that simultaneously address income distribution and poverty alleviation. The paper concludes by proposing policy recommendations grounded in statistical evidence, aimed at promoting inclusive growth and social equity.
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