This paper is concerned with rank-dependent poverty measures and shows that an ordered weighted averaging, hereafter OWA, operator underlies in the definition of these indices. The dual decomposition of an OWA operator into the self-dual core and the anti-self-dual remainder allows us to propose a decomposition for all the rank-dependent poverty measures in terms of incidence, intensity and inequality. In fact, in the poverty field, it is well known that every poverty index should be sensitive to the incidence of poverty, the intensity of poverty and the inequality among the poor individuals. However, the inequality among the poor can be analyzed in terms of either incomes or gaps of the distribution of the poor. And, depending on the side we focus on, contradictory results can be obtained. Nevertheless, the properties inherited by the proposed decompositions from the OWA operators oblige the inequality components to measure equally the inequality of income and inequality of gap overcoming one of the main drawbacks in poverty and inequality measurement. Finally, we provide an empirical illustration showing the appeal of our decompositions for some European Countries in 2005 and 2011. All the rank-dependent poverty measures are written in terms of OWA operators.The decomposition of OWA operators implies the decomposition of poverty measures.The obtained inequality components are consistent.An empirical study for 25 European Countries shows the source of poverty change.
['Oihana Aristondo', 'Mariateresa Ciommi']
The decompositions of rank-dependent poverty measures using ordered weighted averaging operators