Multidimensional Poverty: Measurement, Estimation, and Inference

Oxford Poverty & Human Development Initiative Working Paper No. 47

29 Pages Posted: 26 Jun 2012 Last revised: 27 Jun 2012

See all articles by Christopher Joseph Bennett

Christopher Joseph Bennett

Vanderbilt University

Shabana Mitra

Indian Institute of Management, Bangalore

Date Written: November 1, 2011

Abstract

Multidimensional poverty measures give rise to a host of statistical hypotheses which 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 the minimum P-value methodology of Bennett (2010). 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.

Keywords: Multidimensional poverty, poverty measurement, poverty ordering, Hindus, Muslims

JEL Classification: I32, C12, C14

Suggested Citation

Bennett, Christopher Joseph and Mitra, Shabana, Multidimensional Poverty: Measurement, Estimation, and Inference (November 1, 2011). Oxford Poverty & Human Development Initiative Working Paper No. 47, Available at SSRN: https://ssrn.com/abstract=2093576 or http://dx.doi.org/10.2139/ssrn.2093576

Christopher Joseph Bennett (Contact Author)

Vanderbilt University ( email )

2301 Vanderbilt Place
Nashville, TN 37240
United States

Shabana Mitra

Indian Institute of Management, Bangalore ( email )

Bannerghatta Road
Bangalore, Karnataka 560076
India

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