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Distribution-Sensitive Multidimensional Poverty Measures [electronic resource] : / Datt, Gaurav.

Author/Creator:
Datt, Gaurav.
Other Title:
World Bank working papers.
Publication:
Washington, D.C. : The World Bank, 2018.
Series:
Policy research working papers.
World Bank e-Library.
Format/Description:
Government document
Book
1 online resource (55 p.)
Local subjects:
Crossdimensional Convexity
Multidimensional Poverty
Poverty Assessment
Poverty Measurement
Poverty Reduction
Shapley Decomposition
Transfer Axiom
Summary:
This paper presents axiomatic arguments to make the case for distribution-sensitive multidimensional poverty measures. The commonly-used counting measures violate the strong transfer axiom which requires regressive transfers to be unambiguously poverty-increasing and they are also invariant to changes in the distribution of a given set of deprivations amongst the poor. The paper appeals to strong transfer as well as an additional cross-dimensional convexity property to offer axiomatic justification for distribution-sensitive multidimensional poverty measures. Given the nonlinear structure of these measures, it is al also shown how the problem of an exact dimensional decomposition can be solved using Shapley decomposition methods to assess dimensional contributions to poverty. An empirical illustration for India highlights distinctive features of the distribution-sensitive measures.
Contributor:
Datt, Gaurav.
Other format:
Print Version: Datt, Gaurav.Distribution-Sensitive Multidimensional Poverty Measures
Publisher Number:
10.1596/1813-9450-8346
Access Restriction:
Restricted for use by site license.
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