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Social Choice and Welfare

, Volume 53, Issue 4, pp 677–708 | Cite as

Measuring poverty in multidimensional contexts

  • Iñaki PermanyerEmail author
Original Paper

Abstract

When measuring multidimensional poverty it is reasonable to expect that the trade-offs between variable pairs can differ depending on whether the concerned pairs are complements or substitutes. Yet, currently existing approaches based on deprivation count distributions unrealistically assume that all pairs of variables are related in the same way—an unfortunate circumstance that undermines the possibilities of identifying the poor, aggregating their poverty levels and modeling non-trivial interactions between variables in highly flexible ways. This paper, which aims at modeling non-trivial relational structures across variables both in the identification and aggregation steps, is a first contribution towards addressing these inadequacies. The approach has been axiomatically characterized to flesh out the normative foundations upon which it is based and has a vast potential for application.

Notes

Acknowledgements

Different versions of this paper have been presented at several conferences and seminars (SCW 2014, ECINEQ 2015, SCW 2016): I am grateful to its participants for their valuable comments and suggestions. In particular, I am indebted to Eugenio Peluso, Casilda Lasso de la Vega, Buhong Zheng, Salvador Barberà, Jordi Massó, Sabina Alkire, Suman Seth, Gastón Yalonetzky, Xavi Ramos, Coral del Rio, Olga Alonso-Villar, Carlos Gradín, Rafael Salas, Juan Gabriel Rodriguez and, more generally, to the members of EQUALITAS. The research leading to these results has received funding from the European Research Council (ERC-2014-StG-637768, EQUALIZE project); from the Spanish Ministry of Science, Innovation and Universities ‘Ramón y Cajal’ Research Grant Program (RYC-2013-14196); and its National R&D&I Plan GLOBFAM (RTI2018-096730-B-I00).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Centre d’Estudis DemogràficsBellaterraSpain

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