This paper analyses the effects that income nonresponse has on certain well-known inequality coefficients (e.g. Gini, Theil and Atkinson indexes). A number of statistical methods have been developed to impute missing values of incomes for nonrespondents. By simulating several patterns of income nonresponse on actual sub-samples of the Argentinean household survey, this essay analyses the effects that different correction methods produce on a set of inequality coefficients. It is proved that methods often used to correct for nonresponse can introduce important biases on inequality coefficients if the patterns of missingness assumed by such methods do not coincide with the actual pattern.