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Identifying destitution through linked subsets of multidimensionally poor: An ordinal approach

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  • Sabina Alkire
  • Suman Seth

Abstract

In order to understand whether a reduction in overall poverty has improved the situations of the poorest, it is crucial to distinguish them from the moderately poor population. In this paper, we explore the mechanisms to distinguish subsets of the poor in a multidimensional counting framework. We examine two approaches that capture two distinct forms of stringent multidimensional poverty: one uses a more stringent vector of deprivation cutoffs, and the other, a more stringent cross-dimensional poverty cutoff.

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  • Sabina Alkire & Suman Seth, 2015. "Identifying destitution through linked subsets of multidimensionally poor: An ordinal approach," WIDER Working Paper Series wp-2015-151, World Institute for Development Economic Research (UNU-WIDER).
    • Handle: RePEc:unu:wpaper:wp-2015-151
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    Cited by:

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    2. Alkire, Sabina & Roche, José Manuel & Vaz, Ana, 2017. "Changes Over Time in Multidimensional Poverty: Methodology and Results for 34 Countries," World Development, Elsevier, vol. 94(C), pages 232-249.
    3. Sabina Alkire & Fanni Kövesdi & Elina Scheja & Frank Vollmer, 2023. "Moderate Multidimensional Poverty Index: Paving the Way Out of Poverty," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 168(1), pages 409-445, August.
    4. Sabina Alkire, 2018. "The Research Agenda on Multidimensional Poverty Measurement: Important and As-yet Unanswered Questions," OPHI Working Papers ophiwp119_3.pdf, Queen Elizabeth House, University of Oxford.
    5. Suman Seth and Gaston Yalonetzky, 2018. "Assessing Deprivation with Ordinal Variables: Depth Sensitivity and Poverty Aversion," OPHI Working Papers ophiwp123.pdf, Queen Elizabeth House, University of Oxford.
    6. Abbas, Khizar & Xie, Xiaoqing & Xu, Deyi & Butt, Khalid Manzoor, 2021. "Assessing an empirical relationship between energy poverty and domestic health issues: A multidimensional approach," Energy, Elsevier, vol. 221(C).
    7. Abbas, Khizar & Butt, Khalid Manzoor & Xu, Deyi & Ali, Muhammad & Baz, Khan & Kharl, Sanwal Hussain & Ahmed, Mansoor, 2022. "Measurements and determinants of extreme multidimensional energy poverty using machine learning," Energy, Elsevier, vol. 251(C).
    8. Daoud, Adel & Herlitz, Anders & Subramanian, S.V., 2022. "IMF fairness: Calibrating the policies of the International Monetary Fund based on distributive justice," World Development, Elsevier, vol. 157(C).

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