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On the robustness of multidimensional counting poverty orderings

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journal contribution
posted on 09.12.2019, 12:15 by Fran AzpitarteFran Azpitarte, Jose Gallegos, Gaston Yalonetzky
Counting poverty measures have gained prominence in the analysis of multidimensional poverty in recent decades. Poverty orderings based on these measures typically depend on methodological choices regarding individual poverty functions, poverty cut-offs, and dimensional weights whose impact on poverty rankings is often not well understood. In this paper we propose new dominance conditions that allow the analyst to evaluate the robustness of poverty comparisons to those choices. These conditions provide an approach to evaluating the sensitivity of poverty orderings superior to the common approach of considering a restricted and arbitrary set of indices, cut-offs, and weights. The new criteria apply to a broad class of counting poverty measures widely used in empirical analysis of poverty in developed and developing countries including the multidimensional headcount and the adjusted headcount ratios. We illustrate these methods with an application to time-trends in poverty in Australia and crossregional poverty in Peru. Our results highlight the potentially large sensitivity of poverty orderings based on counting measures and the importance of evaluating the robustness of results when performing poverty comparisons across time and regions.

Funding

Australian Research Council Centre of Excellence for Children and Families over the Life Course (project number CE140100027)

European Regional Development Fund (ECO2016-76506-C4-2-R)

Spanish State Research Agency

History

School

  • Social Sciences

Department

  • Communication, Media, Social and Policy Studies

Published in

The Journal of Economic Inequality

Volume

18

Pages

339 - 364

Publisher

Springer Verlag

Version

VoR (Version of Record)

Rights holder

© The authors

Publisher statement

This is an Open Access Article. It is published by Springer under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

Acceptance date

06/11/2019

Publication date

2020-05-12

Copyright date

2020

ISSN

1569-1721

eISSN

1573-8701

Language

en

Depositor

Dr Fran Azpitarte Deposit date: 6 December 2019