The amp;apos'prediction approachamp;apos' proposed by Dearden, Machin and Reed (DMR) consists in (1) regressing the observed incomes of the child and parent families on separate sets of predetermined variables, and (2) regressing the childamp;apos's predicted income on that of the parents....

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...

Inequality measures are powerful tools of applied welfare analysis. However, to use the tools effectively one has to take into account the characteristics of the data with which one usually has to work. These raise a number of common statistical problems which are addressed here for both...

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...

Specific functional forms are often used in economic models of distributions; goodness-of-fit measures are used to assess whether a functional form is appropriate in the light of real-world data. Standard approaches use a distance criterion based on the EDF, an aggregation of differences in...