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...

Statistical problems in modelling personal income distributions include estimation procedures, testing and model choice. Typically, the parameters of a given model are estimated by classical procedures such as maximum likelihood and least squares estimators. Unfortunately, the classical methods...

Statistical problems in modelling personal income distributions include estimation procedures, testing and model choice. Typically, the parameters of a given model are estimated by classical procedures such as maximum likelihood and least squares estimators. Unfortunately, the classical methods...

Empirical analyses on income and wealth inequality and those in other fields in economics and finance often face the difficulty that the data is heterogeneous, heavy-tailed or correlated in some unknown fashion. The paper focuses on applications of the recently developed \textit{t}-statistic...

In this paper we present a robust parameter estimation method for jointly estimating shape parameter α, scale parameter γ and location parameter δ of a symmetric stable distribution. The proposed estimation method is based on Probability Integral Transformation (PIT) and robust M-estimators....

The concept of breakdown point was introduced by Hodges (1967) and Hampel (1968, 1971) and still plays an important though at times a controversial role in robust statistics. It has proved most successful in the context of location, scale and regression problems. In this paper we argue that this...