Assignment #8

Since I’m interested in the relationship between economic growth and income inequality, I ran a regression on GDP growth and the Gini coefficient, which is a popular measurement for national inequality. I want to see if economic growth will decrease if income inequality increases, which would be considered a negative relationship. While the Gini coefficient is my variable of interest, in my model I also included the unemployment rate, if a recession or war was taking place, political party of the president in office, interest rate, and consumer confidence index. After running the regression, it could be seen that there was a negative relationship between GDP growth and the Gini coefficient since the slope coefficient for the Gini was -21.29. The t statistic for the Gini was -2.36, which suggests that the negative relationship between GDP growth and the Gini is statistically significant. The F statistic tells us that all of the variables as a whole are significant, but individually some of the variables may not be significant because of their low t statistic. The R-squared value tells us that 58% of the variation can be explained in the regression. This suggests that there may be other variables not included in the model that are affecting GDP growth. Therefore, I may have to try different variables in my model, especially since some of the variables are not individually significant.  While I think this regression may give a good indication of the negative relationship between economic growth and income inequality, I do not believe income inequality is causing a decrease in economic growth, especially when there are so many other variables that affect GDP growth.