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Examining multidimensional poverty reduction in India 2005/6–2015/16: Insights and oversights of the headcount ratio

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  • Alkire, Sabina
  • Oldiges, Christian
  • Kanagaratnam, Usha

Abstract

Following Amartya Sen’s pioneering ideas on poverty and inequality measurement, the development economics literature proposes diverse classes of measures as well as poverty orderings. Yet in the Sustainable Development Goals (SDGs), the headcount ratio is the primary statistic for measuring monetary and multidimensional poverty. Rigorously analysing the trends of multidimensional poverty for India between 2005/6 and 2015/16, we illustrate how the headcount ratio is not able to observe certain centrally important requirements of the SDGs – such as whether anyone is being left behind, or how deprivations are interlinked. We propose using the adjusted headcount ratio or Multidimensional Poverty Index (MPI) as the primary poverty measure for policy assessment, supplemented by the headcount ratio, intensity, number of poor, and composition of poverty, to provide more accurate analyses. Exploiting cross-sectional data comprising of more than three million individuals and a panel of 29 states and several socio-economic subgroups, we show empirically how the reduction of multidimensional poverty by 271 million unfolded within a decade. In contrast to earlier periods in time, we find that the poorest of the poor saw the largest reductions in multidimensional poverty due to falling levels of intensity – a feature the headcount ratio alone cannot portray. Despite the importance of the MPI we recognise the inherent and enduring need to probe the headcount ratio and number of poor statistics. Hence we corroborate these stark findings with an assessment of the dominance of the distribution of attainment scores which establishes the relationship between MPI and H in both periods. To assess the robustness of the number of poor leaving poverty, 19 additional MPIs are constructed, each having different indicator definitions and combinations, and it is found that in all but one of these, more than 270 million people left poverty.

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  • Alkire, Sabina & Oldiges, Christian & Kanagaratnam, Usha, 2021. "Examining multidimensional poverty reduction in India 2005/6–2015/16: Insights and oversights of the headcount ratio," World Development, Elsevier, vol. 142(C).
    • Handle: RePEc:eee:wdevel:v:142:y:2021:i:c:s0305750x21000668
    DOI: 10.1016/j.worlddev.2021.105454
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    2. Han, Linsong & Li, Xun & Xu, Gang, 2022. "Anti-corruption and poverty alleviation: Evidence from China," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 150-172.
    3. Tomson Ogwang, 2022. "The regression approach to the measurement and decomposition of the multidimensional Watts poverty index," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(4), pages 951-973, December.
    4. Sudha Narayanan & Christian Oldiges & Shree Saha, 2022. "Does workfare work? India's employment guarantee during COVID‐19," Journal of International Development, John Wiley & Sons, Ltd., vol. 34(1), pages 82-108, January.
    5. Tang, Jianjun & Gong, Jiaowei & Ma, Wanglin & Rahut, Dil Bahadur, 2022. "Narrowing urban–rural income gap in China: The role of the targeted poverty alleviation program," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 74-90.

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