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Endogenous weights and multidimensional poverty: A cautionary tale

Author

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  • Dutta, Indranil
  • Nogales, Ricardo
  • Yalonetzky, Gaston

Abstract

Multidimensional poverty measures have become a standard feature in poverty assessments. A large and growing body of work uses endogenous (data driven) weights to compute multidimensional poverty. We demonstrate that broad classes of endogenous weights violate key properties of poverty indices such as monotonicity and subgroup consistency, without which poverty evaluation and policy targeting are seriously compromised. Using data from Ecuador and Uganda we show that these violations are widespread. Our results can be extended to other composite welfare measures such as the widely used asset indices.

Suggested Citation

  • Dutta, Indranil & Nogales, Ricardo & Yalonetzky, Gaston, 2021. "Endogenous weights and multidimensional poverty: A cautionary tale," Journal of Development Economics, Elsevier, vol. 151(C).
    • Handle: RePEc:eee:deveco:v:151:y:2021:i:c:s0304387821000286
    DOI: 10.1016/j.jdeveco.2021.102649
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    References listed on IDEAS

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    Cited by:

    1. Jhonatan Clausen & Nicolas Barrantes, 2022. "Developing a Comprehensive Multidimensional Wellbeing Index Based on What People Value: An Application to a Middle-Income Country," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 17(6), pages 3253-3283, December.
    2. Fernando Flores Tavares & Gianni Betti, 2024. "Gender Differences in Multidimensional Poverty in Brazil: A Fuzzy Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 175(2), pages 385-422, November.
    3. Francisco Azpitarte & Gaston Yalonetzky, 2023. "The measurement of asset and wealth poverty," Chapters, in: Jacques Silber (ed.), Research Handbook on Measuring Poverty and Deprivation, chapter 38, pages 410-419, Edward Elgar Publishing.
    4. 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.
    5. Yiyan Chen & Zhaoyun Tang, 2023. "A Study of Multidimensional and Persistent Poverty among Migrant Workers: Evidence from China’s CFPS 2014–2020," Sustainability, MDPI, vol. 15(10), pages 1-15, May.
    6. Hlasny, Vladimir & Asadullah, M Niaz & Sabra, Alia, 2022. "The Adoption of the Multidimensional Poverty Index in Developing Asia: Implications for Social Program Targeting and Inequality Reduction," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 56(3), pages 185-195.
    7. Di Tommaso, Marco R. & Prodi, Elena & Pollio, Chiara & Barbieri, Elisa, 2023. "Conceptualizing and measuring “industry resilience”: Composite indicators for postshock industrial policy decision-making," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).

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    Keywords

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    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure

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