In this study we analyze the effects of corruption on income inequality and poverty. Our analysis advances the existing literature in four ways. First, instead of using corruption indices assembled by various investment risk services, we use an objective measure of corruption: the number of public officials convicted in a state for crimes related to corruption. Second, we use all commonly used inequality and poverty measures including various Atkinson indexes, Gini index, standard deviation of the logarithms, relative mean deviation, coefficient of variation, and the poverty rate defined by the U.S. Census Bureau. Third, we minimize the problems which are likely to arise due to data incomparability by examining the differences in income inequality, and poverty across U.S. states. Finally, we exploit both time series and cross sectional variation in the data. We find robust evidence that an increase in corruption increases income inequality and poverty.