We discuss statistical inference problems associated with identification and testability in econometrics, and we emphasize the common nature of the two issues. After reviewing the relevant statistical notions, we consider in turn inference in nonparametric models and recent developments on...

This paper gives an overview of the way the issue of poverty measurement is typically addressed in economics. After having briefly defined what is meant by poverty in economics, I examine successively the unidimensional approach to poverty based on the income or expenses, and the...

Dans cet article, nous proposons des tests sur la forme de la distribution des erreurs dans un modèle de régression linéaire multivarié (RLM). Les tests que nous développons sont fonction des résidus obtenus par moindres carrés multivariés, lesquels sont standardisés de façon à ce que...

In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR) with applications to asset pricing models. We focus on departures from the assumption of i.i.d. errors assumption, at univariate and multivariate levels, with Gaussian and non-Gaussian...

In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the framework of...

La microfinance se développe progressivement dans la région du Moyen-Orient et d’Afrique du Nord (MENA) à travers des institutions de microfinance (IMF) très variées. L’objectif de la plupart de ces IMF est de concilier la performance sociale (PS) qui vise à réduire la pauvreté et la...

In the last decades, Corporate Social Responsibility (CSR) has been deeply studied. Many researchers focused on the best social report form underlining advantages, and they shown that these documents follow more and more often balance-sheets. This work analyses the relation between the writing...