The relationship between income inequality and corruption: An empirical analysis

This thesis aims to analyse the relationship between corruption and income inequality. The analyses are based on a large panel data set of 96 developed and developing countries between 1996 and 2019. Two different methods, two-stage system GMM and QML-FE, are used in the analysis. Income inequality is measured using a set of measures from the World Income Inequality Database (WIID), including the Gini index, various specifications of the Atkinson index, and top and bottom income shares, while Transparency International's Corruption Perceptions Index (CPI) and the World Bank's Corruption Control Percentile Rank (CCR) are used as measures of corruption. The regression analysis results show that corruption has significant distributional implications. The analyses reveal the existence of an asymmetric structure between the variables characterised by an inverted U-shape, similar to the Kuznets hypothesis. While one dimension of this asymmetric structure is consistent with the prevailing literature that corruption and income inequality are positively correlated, the other dimension provides evidence of a negative relationship between corruption and income inequality.