Multidimensional poverty measurement with individual preferences

We propose a new class of multidimensional poverty indices. To aggregate and weight the different dimensions of poverty, we rely on the preferences of the concerned agents rather than on an arbitrary weighting scheme selected by the analyst. The Pareto principle is, therefore, satisfied among the poor. The indices add up individual measures of poverty that are computed as a convex transform of the fraction of the poverty line vector to which the agent is indifferent. The axiomatic characterization of this class is grounded on new principles of interpersonal poverty comparisons and of inequality aversion among the poor. We illustrate our approach with Russian survey data between 1995 and 2005. We find that, compared to standard poverty indices, our preference sensitive indices lead to considerable differences in the identification of the poor and in subgroup poverty comparisons.(This abstract was borrowed from another version of this item.)