Multidimensional Poverty: Measurement, Estimation, and Inference
AbstractMultidimensional poverty measures give rise to a host of statistical hypotheses that are of interest to applied economists and policy-makers alike. In the specific context of the generalized Alkire--Foster (Alkire and Foster, 2008) class of measures, we show that many of these hypotheses can be treated in a unified manner and also tested simultaneously using a minimum p -value approach. When applied to study the relative state of poverty among Hindus and Muslims in India, these tests reveal novel insights into the plight of the poor which are not otherwise captured by traditional univariate approaches.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Econometric Reviews.
Volume (Year): 32 (2013)
Issue (Month): 1 (January)
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Other versions of this item:
- Christopher J. Bennett and Shabana Mitra, 2011. "Multidimensional Poverty: Measurement, Estimation, and Inference," OPHI Working Papers ophiwp047, Queen Elizabeth House, University of Oxford.
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- Yélé Batana, 2013. "Multidimensional Measurement of Poverty Among Women in Sub-Saharan Africa," Social Indicators Research, Springer, vol. 112(2), pages 337-362, June.
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- Sabina Alkire and James Foster, 2011. "Understandings and Misunderstandings of Multidimensional Poverty Measurement," OPHI Working Papers ophiwp043, Queen Elizabeth House, University of Oxford.
- James Foster & Sabina Alkire, 2011. "Understandings and Misunderstandings of Multidimensional Poverty Measurement," Working Papers 2011-18, The George Washington University, Institute for International Economic Policy.
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