This bachelor thesis examines the relationship between corruption and income inequalities and whether if a countries legal system has any impact. Our contribution in this paper was to seek for significant indications by dividing the world`s countries into segments.

Information on the subject of both corruption and income inequalities that is used in this thesis are from several well-cited authors. Data was collected for countries that had suffi- cient data for the GINI coefficient and the corruption index, and where the total ended up to be 99 countries. As a measure for Corruption we used the Corruption Perception Index (CPI), which is gathered by Transparency International and is the far broadest index availa- ble as per today. Important to take into account is the difficulty of gathering accurate and high qualitative data on the subject of corruption, as it is illegal and often of hidden nature. So therefore the interest in this paper has been the perceived level of corruption in any country, which makes the CPI fit our model the best.

For the GINI coefficient, which is a measure of income inequality, data has been collected from the World Income Inequality Database 2 (WIID2).

We used a Weighted Least Square (WLS) regression method throughout the paper. One of the reasons for a WLS regression among others was to deal with our heteroscedasticity. In order to get a balanced dataset and to avoid short-run fluctuations the regressions are based on a five-year average between the years 2002 and 2006.

What we find is significant result measuring the CPI against GINI. By using the WLS method we had good results in the values of R2 and Std. Error of the Estimate. When in- cluding the dummy variables such as French, Scandinavian, Socialist or English, none of these dummies showed any significant results. However, we found significant results when all cases were tested individually between the CPI and the GINI coefficient for each specif- ic segment.