Multidimensional poverty measurement with individual preferences

We propose a new approach to multidimensional poverty measurement. To aggregate and weight the different dimensions of poverty, we rely on the preferences of the concerned individuals rather than on an arbitrary weighting scheme selected by the analyst. We provide an axiomatic characterization of an approach in which multidimensional poverty measures add up individual indices of poverty based on their multidimensional outcomes and their preferences. We discuss two families of these individual indices of poverty: quantity metrics and money metrics. Members of the first family evaluate individual poverty by the fraction of the poverty line vector to which the individual is indifferent. The second family considers the ratio between the income to which the individual is indifferent, for some fixed price vector, and the money value of the poverty line vector. 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.