In most health survey the state of health of individuals is measured through several different kinds of variables such as qualitative, discrete quantitative or dichotomic ones. From these variables, one aims at building univariate indices of health that summarize the information. To do so, we...

Generalized Linear Latent Variables Models (GLLVM) enable the modeling of relationships between manifest and latent variables, where the manifest variables are distributed according to a distribution of the exponential family (e.g. binomial or normal) and to the multinomial distribution (for...

In most health survey the state of health of individuals is measured through several different kinds of variables such as qualitative, discrete quantitative or dichotomic ones. From these variables, one aims at building univariate indices of health that summarize the information. To do so, we...

In this paper, we discuss one of the reasons leading practitionners to the rejection of the Markowitz model and propose a new stastistical method to avoid this problem. To be more precise, we discuss the problem of statistical robustness of the Markowitz optimizer and show that the latter is not...

Poverty analysis in Tunisia so far depends heavily upon the choice of poverty lines. In this paper we propose to adopt an approach based on the determination of regional basic needs in order to estimte the differential between urban and rural lines. In order to get stable results we also propose...

In this paper, we study the finite sample accuracy of confidence intervals for index functional built via parametric bootstrap, in the case of inequality indices. To estimate the parameters of the assumed parametric data generating distribution, we propose a Generalized Method of Moment...

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...