Elin Magnusson: An analysis of the relationship between income inequality and indicators of social and infrastructural development

In this paper a multiple regression analysis will be undertaken to examine which social and infrastructural indicators best explain and predict income inequality. To quantify income inequality, the Gini coeffcient is used. The analysis is made on two separate data sets with different ways of measuring income. In the first data set the income from countries worldwide is calculated on the basis of household per capita, while in the second set it is calculated for OECD countries on a modified scale. The two data sets reach between the years 1990 and 2006. The explanatory variables are basic indicators for development such as age and population demographics, school enrolment and infrastructural factors. In the regression analysis it is shown that models for explaining income inequality can be found but that exact predictions cannot be made. Variables used in both final models include Life expectancy, Urban population and Infant mortality rate. Additionally, age demographic variables are used in both models but the demographic variable used differs between the two.