Azpitarte2020_Article_OnTheRobustnessOfMultidimensio.pdf (638.48 kB)
On the robustness of multidimensional counting poverty orderings
journal contribution
posted on 2019-12-09, 12:15 authored by Fran AzpitarteFran Azpitarte, Jose Gallegos, Gaston YalonetzkyCounting 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 InequalityVolume
18Pages
339 - 364Publisher
Springer VerlagVersion
- VoR (Version of Record)
Rights holder
© The authorsPublisher 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
2019-11-06Publication date
2020-05-12Copyright date
2020ISSN
1569-1721eISSN
1573-8701Publisher version
Language
- en
Depositor
Dr Fran Azpitarte Deposit date: 6 December 2019Usage metrics
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