In this paper we propose a robust version of Cox-type test statistics for the choice between two non-nested hypotheses. We first show that the influence of small amounts of contamination in the data on the test decision can be very large. Secondly we build a robust test statistic by using the...

n this paper robustness properties of the maximum likelihood estimator (MLE) and several robust estimators for the logistic regression model when the responses are binary are analysed analytically by means of the Influence Function (IF) and empirically by means of simulations. It is found that...

Giovanni Giorgi’s chapter on the sampling properties of inequality indices concentrates upon reviewing the different contributions to the subject. It is certainly a useful collection of bibliographical references for the researcher interested in a complete statistical analysis of income data...

n this paper, we consider the problem of outliers in incomplete multivariate data, when the aim is to estimate a measure of mean and covariance as it is the case for example in factor analysis. In such a situation the ER algorithm of Little and Smith (1987) which combines the EM algorithm for...

For manifest variables with additive noise and for a given number of latent variables with an assumed distribution, we propose to nonparametrically estimate the association between latent and manifest variables. Our estimation is a two step procedure: First it employs standard factor analysis to...

We review the use and the interpretation of some robustness concepts and techniques in some economic applications. We focus on estimation techniques in income distribution analysis and we discuss the reliability of inequality measures

The paper discusses the effect of model deviations such as data contamination on the maximum likelihood estimator (MLE) for a general class of latent trait models (citeNP{MoKn:00}). This is done with the use of the influence function (Hampel 1968, 1974) a mathematical tool to assess the...

Robust statistics, as a concept, probably dates back to the prehistory of statistics. It has, however, been formalized in the sixties by the pioneering work of Huber and Hampel. Robust statistics is an extension of classical statistics, which takes into account the fact that models assumed to...

Poverty analysis often results in the computation of poverty indexes based on so-called poverty lines which can be region speci…c poverty lines. The poverty lines are made of two components, namely the amount of income to satisfy the food and the non food needs. For both components, one needs...

In this paper robustness properties of the maximum likelihood estimator (MLE) and several robust estimators for the logistic regression model when the responses are binary are analysed. It is found that the MLE and the classical Rao's score test can be misleading in the presence of model...