Deprivation and the dimnensionality of welfare : a variable-selection cluster-analysis approach

In this paper we tackle the problems of dimensionality of welfare and that of identifying the multidimensionally poor by first finding the poor using the original space of attributes, and then reducing the welfare space. The starting point is the notion that the "poor" constitutes a group of individuals that are essentially different from the "non-poor" in a truly multidimensional framwework. Once this group has been identified, we propose reducing the dimension of the original welfare space by solving the problem of finding the smallest set of attributes that can reproduce as accurately as possible the "poor/non-poor" classification in the first stage. -- Multidimensional welfare ; poverty ; factory analysis ; clusters