Inequality measures are often used to summarise information about empirical income distributions. However, the resulting picture of the distribution and of the changes in the distribution can be severely distorted if the data are contaminated. The nature of this distortion will in general depend...

Modelling Lorenz curves (LC) for stochastic dominance comparisons is central to the analysis of income distribution. It is conventional to use non-parametric statistics based on empirical income cumulants which are in the construction of LC and other related second-order dominance criteria....

With income distributions it is common to encounter the problem of missing data. When a parametric model is fitted to the data, the problem can be overcome by specifying the marginal distribution of the observed data. With classical methods of estimation such as the maximum likelihood (ML) an...

Distributional dominance criteria are commonly applied to draw welfare inferences about comparisons, but conclusions drawn from empirical implementations of dominance criteria may be influenced by data contamination. We examine a non-parametric approach to refining Lorenz-type comparisons and...

Lorenz curves and second-order dominance criteria are known to be sensitive to data contamination in the right tail of the distribution. We propose two ways of dealing with the problem: (1) Estimate Lorenz curves using parametric models for income distributions, and (2) Combine empirical...

Lorenz curves and associated tools for ranking income distributions are commonly estimated on the assumption that full, unbiased samples are available. However, it is common to find income and wealth distributions that are routinely censored or trimmed. We derive the sampling distribution for a...

This paper presents a robust estimation of two income distribution models using Spanish data for the period 1990-91 under three different concepts of income. The effect on the estimates of the Theil index due to the choice of the definition of income and of the estimation method is also analysed

Choosing between two income distribution models typically involves testing two non-tested hypotheses, that is hypotheses such that one cannot be obtained as a special or limiting case of the other. Cox (1961, 1962) proposed a classical testing procedure based on the comparison of the maximised...

An important aspect of income distribution is the modelling of the data using an appropriate parametric model. This involves estimating the parameters of the models, given the data at hand. Income data are typically in grouped form. Moreover, they are not always reliable in that they may contain...

The economic analysis of income distribution and related topics makes extensive use of dominance criteria to draw inferences about welfare comparisons. However it is possible that - just as some inequality statistics can be very sensitive to extreme values - conclusions drawn from empirical...