  In this study, we extend the research on the dynamic poverty indexes, namely
the dynamic Headcount ratio, the dynamic income-gap ratio, the dynamic Gini and
the dynamic Sen, proposed in D'Amico and Regnault (2018). The contribution is
twofold. First, we extend the computation of the dynamic Gini index, thus the
Sen index accordingly, with the inclusion of the inequality within each class
of poverty where people are classified according to their income. Second, for
each poverty index, we establish a central limit theorem that gives us the
possibility to determine the confidence sets. An application to the Italian
income data from 1998 to 2012 confirms the effectiveness of the considered
approach and the possibility to determine the evolution of poverty and
inequality in real economies.
