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 among 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 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: | Journal Article biblioteca |
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Published by Oxford University Press on behalf of the World Bank
2019-10
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| Subjects: | POVERTY MEASUREMENT, TRANSFER AXIOM, CROSS-DIMENSIONAL CONVEXITY, SHAPLEY DECOMPOSITION, INCOME DISTRIBUTION, MULTIDIMENSIONAL POVERTY, |
| Online Access: | http://hdl.handle.net/10986/35396 |
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dig-okr-10986353962021-04-23T14:02:21Z 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 among 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 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. 2021-04-07T20:15:25Z 2021-04-07T20:15:25Z 2019-10 Journal Article World Bank Economic Review 1564-698X http://hdl.handle.net/10986/35396 CC BY-NC-ND 3.0 IGO http://creativecommons.org/licenses/by-nc-nd/3.0/igo World Bank Published by Oxford University Press on behalf of the World Bank Publications & Research :: Journal Article Publications & Research South Asia India |
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| topic |
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 among 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 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 |
Journal Article |
| 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 |
Published by Oxford University Press on behalf of the World Bank |
| publishDate |
2019-10 |
| url |
http://hdl.handle.net/10986/35396 |
| work_keys_str_mv |
AT dattgaurav distributionsensitivemultidimensionalpovertymeasures |
| _version_ |
1756575838673829888 |