Distribution-Sensitive Multidimensional Poverty Measures
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.
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Format: | Working Paper biblioteca |
Language: | English |
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World Bank, Washington, DC
2018-02
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Subjects: | POVERTY MEASUREMENT, TRANSFER AXIOM, CROSS-DIMENSIONAL CONVEXITY, SHAPLEY DECOMPOSITION, INCOME DISTRIBUTION, MULTIDIMENSIONAL POVERTY, |
Online Access: | http://documents.worldbank.org/curated/en/156261519136911696/Distribution-sensitive-multidimensional-poverty-measures https://hdl.handle.net/10986/29406 |
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dig-okr-10986294062024-08-09T08:05:56Z Distribution-Sensitive Multidimensional Poverty Measures Datt, Gaurav POVERTY MEASUREMENT TRANSFER AXIOM CROSS-DIMENSIONAL CONVEXITY SHAPLEY DECOMPOSITION INCOME DISTRIBUTION MULTIDIMENSIONAL POVERTY 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. 2018-02-28T22:30:22Z 2018-02-28T22:30:22Z 2018-02 Working Paper Document de travail Documento de trabajo http://documents.worldbank.org/curated/en/156261519136911696/Distribution-sensitive-multidimensional-poverty-measures https://hdl.handle.net/10986/29406 English Policy Research Working Paper;No. 8346 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank application/pdf text/plain World Bank, Washington, DC |
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POVERTY MEASUREMENT TRANSFER AXIOM CROSS-DIMENSIONAL CONVEXITY SHAPLEY DECOMPOSITION INCOME DISTRIBUTION MULTIDIMENSIONAL POVERTY POVERTY MEASUREMENT TRANSFER AXIOM CROSS-DIMENSIONAL CONVEXITY SHAPLEY DECOMPOSITION INCOME DISTRIBUTION MULTIDIMENSIONAL POVERTY |
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POVERTY MEASUREMENT TRANSFER AXIOM CROSS-DIMENSIONAL CONVEXITY SHAPLEY DECOMPOSITION INCOME DISTRIBUTION MULTIDIMENSIONAL POVERTY POVERTY MEASUREMENT TRANSFER AXIOM CROSS-DIMENSIONAL CONVEXITY SHAPLEY DECOMPOSITION INCOME DISTRIBUTION MULTIDIMENSIONAL POVERTY Datt, Gaurav Distribution-Sensitive Multidimensional Poverty Measures |
description |
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. |
format |
Working Paper |
topic_facet |
POVERTY MEASUREMENT TRANSFER AXIOM CROSS-DIMENSIONAL CONVEXITY SHAPLEY DECOMPOSITION INCOME DISTRIBUTION MULTIDIMENSIONAL POVERTY |
author |
Datt, Gaurav |
author_facet |
Datt, Gaurav |
author_sort |
Datt, Gaurav |
title |
Distribution-Sensitive Multidimensional Poverty Measures |
title_short |
Distribution-Sensitive Multidimensional Poverty Measures |
title_full |
Distribution-Sensitive Multidimensional Poverty Measures |
title_fullStr |
Distribution-Sensitive Multidimensional Poverty Measures |
title_full_unstemmed |
Distribution-Sensitive Multidimensional Poverty Measures |
title_sort |
distribution-sensitive multidimensional poverty measures |
publisher |
World Bank, Washington, DC |
publishDate |
2018-02 |
url |
http://documents.worldbank.org/curated/en/156261519136911696/Distribution-sensitive-multidimensional-poverty-measures https://hdl.handle.net/10986/29406 |
work_keys_str_mv |
AT dattgaurav distributionsensitivemultidimensionalpovertymeasures |
_version_ |
1807156913932075008 |