When health status is an ordered response variable, Allison and Foster (2004) postulate that a distribution Q exhibits more inequality than a distribution P if Q isobtained from P via a sequence of median preserving spreads. This paper introduces aparametric family of inequality indices which...

To date, inequality orderings for ordered response data are only suitable for comparing distributions that share a common median state. In this paper we propose a methodology for comparing distributions irrespective of their medians. We set out to do so by introducing a general pre-ordering and...

Because the permanent incomes of parents and children are typically unobserved, the estimation of the intergenerational correlation via the use of proxy variables entails an errors-in-variables bias. By solving a system of moment equations for income observed at a given year, and a T-period...

Averaging methods are routinely used in order to limit biases resulting from the mismeasurement of permanent incomes. The Solon/Zimmerman estimator regresses a single-year measurement of the child's resources on a T-period average of the parents' income while the Behrman/Taubman estimator...

We contrast two approaches to the prediction of latent variables in the model of factor analysis. The likelihood statistic is a sufficient statistic for the unobservables when sampling arises from the exponential family of distributions. Linear predictors, on the other hand, can be obtained as...

The standard approach to the study of poverty assumes the existence of an ideal variable that captures the extent of deprivation. In this paper we postulate that poverty is involved with many dimensions. We use a latent variable framework to predict the extent of an individual's hardship as a...

The 'prediction approach' 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 child's predicted income on that of the parents. Conceptually, this estimator...