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Global Poverty Estimates: A Sensitivity Analysis

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  • Dhongde, Shatakshee
  • Minoiu, Camelia

Abstract

Current estimates of global poverty vary substantially across studies. We undertake a sensitivity analysis to highlight the importance of methodological choices by measuring global poverty using different data sources, parametric and nonparametric estimation methods, and multiple poverty lines. Our results indicate that estimates of global poverty vary significantly when they are based alternately on data from household surveys versus national accounts but are relatively consistent across estimation methods. The decline in poverty over the past decade is found to be robust across methodological choices.

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  • Dhongde, Shatakshee & Minoiu, Camelia, 2013. "Global Poverty Estimates: A Sensitivity Analysis," World Development, Elsevier, vol. 44(C), pages 1-13.
    • Handle: RePEc:eee:wdevel:v:44:y:2013:i:c:p:1-13
    DOI: 10.1016/j.worlddev.2012.12.010
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    2. Stein, Alexander J., 2013. "Rethinking the measurement of undernutrition in a broader health context: Should we look at possible causes or actual effects:," IFPRI discussion papers 1298, International Food Policy Research Institute (IFPRI).
    3. Vanesa Jorda & José María Sarabia & Markus Jäntti, 2021. "Inequality measurement with grouped data: Parametric and non‐parametric methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 964-984, July.
    4. Vanesa Jorda & Jos Mar a Sarabia & Markus J ntti, 2020. "Estimation of Income Inequality from Grouped Data," LIS Working papers 804, LIS Cross-National Data Center in Luxembourg.
    5. Alkire, Sabina & Santos, Maria Emma, 2014. "Measuring Acute Poverty in the Developing World: Robustness and Scope of the Multidimensional Poverty Index," World Development, Elsevier, vol. 59(C), pages 251-274.
    6. Armando Barrientos, 2016. "Inequality, Poverty, and Antipoverty Transfers," Working Papers id:11190, eSocialSciences.
    7. Christoph Lakner & Daniel Gerszon Mahler & Mario Negre & Espen Beer Prydz, 2022. "How much does reducing inequality matter for global poverty?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(3), pages 559-585, September.
    8. Moatsos, Michail, 2020. "Global Absolute Poverty: The Evolution of its Measurement," EconStor Preprints 216642, ZBW - Leibniz Information Centre for Economics.
    9. Achille Lemmi & Donatella Grassi & Alessandra Masi & Nicoletta Pannuzi & Andrea Regoli, 2019. "Methodological Choices and Data Quality Issues for Official Poverty Measures: Evidences from Italy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 299-330, January.
    10. Crombrugghe, D.P.I. de & Szirmai, A. & Bluhm, R., 2014. "Poor trends: The pace of poverty reduction after the Millennium Development Agenda," MERIT Working Papers 2014-006, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    11. Moatsos, Michail & Lazopoulos, Achillefs, 2021. "Global poverty: A first estimation of its uncertainty," World Development Perspectives, Elsevier, vol. 22(C).
    12. Bolch, Kimberly B. & Ceriani, Lidia & López-Calva, Luis F., 2022. "The arithmetics and politics of domestic resource mobilization for poverty eradication," World Development, Elsevier, vol. 149(C).
    13. Yoshida, Nobuo & Uematsu, Hiroki & Sobrado, Carlos E., 2014. "Is extreme poverty going to end ? an analytical framework to evaluate progress in ending extreme poverty," Policy Research Working Paper Series 6740, The World Bank.
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    16. Moatsos Michail, 2016. "Global Absolute Poverty: Behind the Veil of Dollars," Journal of Globalization and Development, De Gruyter, vol. 7(2), pages 1-28, December.

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