Income inequality regression models with applications

Abstract: This thesis addresses three topics in income inequality. First, a cross- sectional dataset of 30 countries is used to investigate the causes of between- country differences in income inequality. Secondly, a panel of the same countries is used to examine the drivers behind the change in inequality between 1985 and 2013. This part of the thesis utilizes dynamic regres- sion models for panel data, and compares the estimates from the two most common dynamic panel models. The problem of endogenity of explana- tory variables is addressed, and possible solutions to this problem are dis- cussed, with an emphasis on techniques based on the generalized method of moments (GMM). The main findings are that the trade-to-GDP ratio, the industrial employment share and the political color of the government are the most important explanatory variables of income inequality over time. The final question addressed in the thesis concerns cross-country income inequality convergence over time. Notably, inequality is shown to converge at slightly slower rate than reported by previous studies.