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Did Poverty Reduction Reach the Poorest of the Poor? Complementary Measures of Poverty and Inequality in the Counting Approach

In: Research on Economic Inequality

Author

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  • Suman Seth
  • Sabina Alkire

Abstract

A number of multidimensional poverty measures that respect the ordinal nature of dimensions have recently been proposed within the counting approach framework. Besides ensuring a reduction in poverty, however, it is important to monitor distributional changes to ensure that poverty reduction has been inclusive in reaching the poorest. Distributional issues are typically captured by adjusting a poverty measure to be sensitive to inequality among the poor. This approach, however, has certain practical and conceptual limitations. It conflicts, for example, with some policy-relevant measurement features, such as the ability to decompose a measure into dimensions post-identification and does not create an appropriate framework for assessing disparity in poverty across population subgroups. In this chapter, we propose and justify the use of a separate decomposable inequality measure – a positive multiple of “variance” – to capture the distribution of deprivations among the poor and to assess disparity in poverty across population subgroups. We demonstrate the applicability of our approach through two contrasting inter-temporal illustrations using Demographic Health Survey data sets for Haiti and India.

Suggested Citation

  • Suman Seth & Sabina Alkire, 2017. "Did Poverty Reduction Reach the Poorest of the Poor? Complementary Measures of Poverty and Inequality in the Counting Approach," Research on Economic Inequality, in: Research on Economic Inequality, volume 25, pages 63-102, Emerald Group Publishing Limited.
  • Handle: RePEc:eme:reinzz:s1049-258520170000025005
    DOI: 10.1108/S1049-258520170000025005
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    Citations

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    Cited by:

    1. Jaskirat Singh & Dhiraj Sharma & Gurdip Singh Batra, 2023. "Does Credit Utilization Pattern Promote Poverty Alleviation? An Evidence from India," Global Business Review, International Management Institute, vol. 24(6), pages 1227-1250, December.
    2. Sam Jones, 2022. "Extending multidimensional poverty identification: from additive weights to minimal bundles," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(2), pages 421-438, June.

    More about this item

    Keywords

    Inequality decomposition; inequality among the poor; multidimensional poverty; counting approach; variance decomposition; Haiti; India; D63; O1; I32;
    All these keywords.

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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