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Multidimensional Poverty: Measurement, Estimation, and Inference

Author

Listed:
  • Christopher J. Bennett
  • Shabana Mitra

Abstract

Multidimensional poverty measures give rise to a host of statistical hypotheses that are of interest to applied economists and policy-makers alike. In the specific context of the generalized Alkire--Foster (Alkire and Foster, 2008) class of measures, we show that many of these hypotheses can be treated in a unified manner and also tested simultaneously using a minimum p -value approach. When applied to study the relative state of poverty among Hindus and Muslims in India, these tests reveal novel insights into the plight of the poor which are not otherwise captured by traditional univariate approaches.

Suggested Citation

  • Christopher J. Bennett & Shabana Mitra, 2013. "Multidimensional Poverty: Measurement, Estimation, and Inference," Econometric Reviews, Taylor & Francis Journals, vol. 32(1), pages 57-83, January.
    • Handle: RePEc:taf:emetrv:v:32:y:2013:i:1:p:57-83
    DOI: 10.1080/07474938.2012.690331
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    References listed on IDEAS

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    1. Russell Davidson & Jean-Yves Duclos, 2013. "Testing for Restricted Stochastic Dominance," Econometric Reviews, Taylor & Francis Journals, vol. 32(1), pages 84-125, January.
    2. repec:qeh:ophiwp:ophiwp013 is not listed on IDEAS
    3. repec:qeh:ophiwp:ophiwp014 is not listed on IDEAS
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    Cited by:

    1. Maitra, Chandana & Rao, D.S. Prasada, 2015. "Poverty–Food Security Nexus: Evidence from a Survey of Urban Slum Dwellers in Kolkata," World Development, Elsevier, vol. 72(C), pages 308-325.
    2. Wang, Zihan & Li, Jiaxin & Liu, Jing & Shuai, Chuanmin, 2020. "Is the photovoltaic poverty alleviation project the best way for the poor to escape poverty? ——A DEA and GRA analysis of different projects in rural China," Energy Policy, Elsevier, vol. 137(C).
    3. Daniel Nowak & Christoph Scheicher, 2017. "Considering the Extremely Poor: Multidimensional Poverty Measurement for Germany," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(1), pages 139-162, August.
    4. David Lander & David Gunawan & William Griffiths & Duangkamon Chotikapanich, 2020. "Bayesian assessment of Lorenz and stochastic dominance," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 767-799, May.
    5. Robano, Virginia & Smith, Stephen C., 2013. "Multidimensional Targeting and Evaluation: A General Framework with an Application to a Poverty Program in Bangladesh," IZA Discussion Papers 7593, IZA Network @ LISER.
    6. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2022. "Stochastic dominance spanning and augmenting the human development index with institutional quality," Annals of Operations Research, Springer, vol. 315(1), pages 341-369, August.
    7. Yulin Zhou & Lulu Wei & Feng Lan & Xiang Li & Jing Bian, 2022. "Evaluation and Optimization on Urban Regeneration Sustainability from the Perspective of Multidimensional Welfare of Resettled Resident—Evidence from Resettlement Communities in Xi’an, China," Land, MDPI, vol. 11(8), pages 1-17, August.
    8. repec:qeh:ophiwp:ophiwp065 is not listed on IDEAS
    9. Rolf Aaberge & Andrea Brandolini, 2014. "Multidimensional poverty and inequality," Discussion Papers 792, Statistics Norway, Research Department.
    10. Christoph Bader & Sabin Bieri & Urs Wiesmann & Andreas Heinimann, 2016. "Differences Between Monetary and Multidimensional Poverty in the Lao PDR: Implications for Targeting of Poverty Reduction Policies and Interventions," Poverty & Public Policy, John Wiley & Sons, vol. 8(2), pages 171-197, June.
    11. Ke-Mei Chen & Chao-Hsien Leu & Te-Mu Wang, 2019. "Measurement and Determinants of Multidimensional Poverty: Evidence from Taiwan," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(2), pages 459-478, September.
    12. Nowak, Daniel & Scheicher, Christoph, 2014. "Considering the extremely poor: Multidimensional poverty measurement for Germany," Discussion Papers in Econometrics and Statistics 02/14, University of Cologne, Institute of Econometrics and Statistics.
    13. Maureen Berner, 2017. "Multidimensional Measures of Poverty: The Potential Contribution of Non‐Profit Food Pantry Data to Assess Community Economic Condition," Poverty & Public Policy, John Wiley & Sons, vol. 9(4), pages 381-401, December.
    14. David Lander & David Gunawan & William E. Griffiths & Duangkamon Chotikapanich, 2016. "Bayesian Assessment of Lorenz and Stochastic Dominance Using a Mixture of Gamma Densities," Department of Economics - Working Papers Series 2023, The University of Melbourne.
    15. Tahsin Mehdi, 2019. "Stochastic Dominance Approach to OECD’s Better Life Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(3), pages 917-954, June.
    16. 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.
    17. Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2020. "On the construction of a feasible range of multidimensional poverty under benchmark weight uncertainty," European Journal of Operational Research, Elsevier, vol. 281(2), pages 415-427.

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