| Popis: |
The effects of globalization on global inequality have been a much-discussed topic for decades. This paper contributes to the debate by providing a data-based, up-to-date analysis on the most important factors of globalization and inequality. The examination is done by computing a linear regression model via R Studio to see whether there is a correlation between the Foreign Trade Ratio and the GINI Coefficient. Alternative variables that are included are the GDP/capita, the national employment rate and the population’s median age. The independent variable (Foreign Trade Ratio) and the dependent variable (GINI Coefficient) are analyzed in three steps. The first step is to perform a descriptive analysis. With this central tendencies, dispersion and distribution of the variables are determined separately. Secondly, a bivariate regression analysis links the dependent variable to the independent variable to show whether there is a significant connection. Thirdly, a multivariate model adds GDP/capita, employment rate and the population’s median age to the regression model. The analysis shows that trade has a high negative impact on the GINI Coefficient. Based on the results, it can be concluded that a higher FTR correlates with a lower GINI Coefficient, which implies that more trade correlates with less income inequality. Additional findings are that trade, employment, and median age together explain over 40% of the Coefficient’s variation. However, while there is, of course, still room for further investigations to increase the explanation rate, this would exceed the scope of this paper and must be left to later works. |
