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Multidimensional Poverty: Measurement, Estimation, and Inference

  • Christopher J. Bennett and Shabana Mitra

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.

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File URL: http://www3.qeh.ox.ac.uk/pdf/ophiwp/OPHIWP047.pdf
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Paper provided by Queen Elizabeth House, University of Oxford in its series OPHI Working Papers with number ophiwp047.

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Date of creation: Nov 2011
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Handle: RePEc:qeh:ophiwp:ophiwp047
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  1. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
  2. Esfandiar Maasoumi & Maria Ana Lugo, 2008. "The Information Basis of Multivariate Poverty Assessments," Emory Economics 0804, Department of Economics, Emory University (Atlanta).
  3. Bhattacharya, Debopam, 2007. "Inference on inequality from household survey data," Journal of Econometrics, Elsevier, vol. 137(2), pages 674-707, April.
  4. 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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