This paper evaluates multidimensional poverty in European countries introducing two main novelties compared with the previous literature: first, the dimensions of poverty are selected on the basis of the shared values included in the Charter of Fundamental Rights of the European Union; second, the whole space of feasible weights is used to summarise the multidimensional information, in order to remain agnostic about the importance given to the different deprivations. Using data from four waves of EU-SILC, the methodological innovations introduced here have allowed to produce a family of measures that capture the individual probability of being multidimensionally poor. Individual probabilities are then used to analyse the within and between distribution of multidimensional poverty in ten countries. Finally, they get combined with the generalised Lorenz dominance techniques in order to derive socially preferred distributions with the minimum load of value judgments. The novel methods proposed in this analysis allow to move from a dual definition of poverty, where poor and non-poor individuals are classified in a mutually exclusive context, to a continuous measure of deprivation, which allows to capture both the extensive and intensive margin of multidimensional poverty.

The probability of multidimensional poverty in the European Union

Francesca Tosi
2020

Abstract

This paper evaluates multidimensional poverty in European countries introducing two main novelties compared with the previous literature: first, the dimensions of poverty are selected on the basis of the shared values included in the Charter of Fundamental Rights of the European Union; second, the whole space of feasible weights is used to summarise the multidimensional information, in order to remain agnostic about the importance given to the different deprivations. Using data from four waves of EU-SILC, the methodological innovations introduced here have allowed to produce a family of measures that capture the individual probability of being multidimensionally poor. Individual probabilities are then used to analyse the within and between distribution of multidimensional poverty in ten countries. Finally, they get combined with the generalised Lorenz dominance techniques in order to derive socially preferred distributions with the minimum load of value judgments. The novel methods proposed in this analysis allow to move from a dual definition of poverty, where poor and non-poor individuals are classified in a mutually exclusive context, to a continuous measure of deprivation, which allows to capture both the extensive and intensive margin of multidimensional poverty.
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Paolo Liberati, Giuliano Resce, Francesca Tosi
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/727022
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