Income inequality analysis: Panel data approach

Salome Kharebava

Master's thesis

Anotácia:

This paper analyzes income inequality and the potential economic and social factors that contribute to it through the use of panel data analysis. It compares various methods of measuring income inequality and investigates how income inequality is related to economic development, education, the labor market, globalization, and demographic changes. The research specifically concentrates on high-income countries and employs the Gini coefficient and Palma ratio as independent variables in two regression models. The paper highlights potential limitations and sources of error in the analysis and proposes future research directions, including the use of mixed effects modeling and dynamic long panel models. The conclusions drawn from this study may have important implications for policymakers looking to address income inequality.

Abstract:

This paper analyzes income inequality and the potential economic and social factors that contribute to it through the use of panel data analysis. It compares various methods of measuring income inequality and investigates how income inequality is related to economic development, education, the labor market, globalization, and demographic changes. The research specifically concentrates on high-income countries and employs the Gini coefficient and Palma ratio as independent variables in two regression models. The paper highlights potential limitations and sources of error in the analysis and proposes future research directions, including the use of mixed effects modeling and dynamic long panel models. The conclusions drawn from this study may have important implications for policymakers looking to address income inequality.

Kľúčové slová

Gini coefficient, Income Inequality, Panel Data Estimators

Keywords

Gini coefficient, Panel Data Estimators, Income Inequality

Jazyk práce: English

Datum vytvoření / odevzdání či podání práce: 30. 4. 2023

Obhajoba závěrečné práce

• Obhajoba proběhla 5. 6. 2023
• Vedúci: Tomáš Formánek
• Oponent: Vladimír Holý

Vysoká škola ekonomická v Praze

Master programme / odbor:
Economic Data Analysis / Data Analysis and Modeling