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Polarization Of The Poor: Multivariate Relative Poverty Measurement Sans Frontiers

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  • Gordon Anderson

Abstract

A major impediment to poverty evaluation in environments with a multiplicity of wellbeing indicators is the difficulty associated with formulating a poverty frontier in many dimensions. This paper proposes two multivariate relative polarization measures which, in appropriate circumstances, serve as multivariate poverty measures which do not require computation of a poverty frontier. As poverty measures they have the intuitive appeal of reflecting the degree to which poor and non‐poor societies are polarized. (The measures would also have considerable application in studying multivariate convergence issues in economic growth models.) The measures are exemplified in a poor–non‐poor country study over the period 1990–2005, based upon the joint distribution of per capita GNP and Life Expectancy. The results suggest that as a group, the world's poor are experiencing diminished poverty polarization; however, within the world's poor the African nations are experiencing increased poverty polarization.

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  • Gordon Anderson, 2010. "Polarization Of The Poor: Multivariate Relative Poverty Measurement Sans Frontiers," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(1), pages 84-101, March.
    • Handle: RePEc:bla:revinw:v:56:y:2010:i:1:p:84-101
    DOI: 10.1111/j.1475-4991.2009.00364.x
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    7. Gordon Anderson & Oliver Linton & Yoon-Jae Wang, 2009. "Non Parametric Estimation of a Polarization Measure," Working Papers tecipa-363, University of Toronto, Department of Economics.
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    Cited by:

    1. Anderson, Gordon, 2011. "Polarization measurement and inference in many dimensions when subgroups can not be identified," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 5, pages 1-19.
    2. Gordon Anderson & Alessio Farcomeni & Grazia Pittau & Roberto Zelli, 2014. "A new approach to measuring and studying the characteristics of class membership: The progress of poverty, inequality and polarization of income classes in urban China," Working Papers tecipa-521, University of Toronto, Department of Economics.
    3. Chiara Gigliarano & Pietro Muliere, 2012. "Measuring Income Polarization Using an Enlarged Middle Class," Working Papers 271, ECINEQ, Society for the Study of Economic Inequality.
    4. Martin Ravallion, 2012. "Mashup Indices of Development," The World Bank Research Observer, World Bank, vol. 27(1), pages 1-32, February.
    5. Gordon Anderson & Maria Grazia Pittau & Roberto Zelli & Jasmin Thomas, 2018. "Income Inequality, Cohesiveness and Commonality in the Euro Area: A Semi-Parametric Boundary-Free Analysis," Econometrics, MDPI, vol. 6(2), pages 1-20, March.
    6. Anderson, Gordon & Linton, Oliver & Whang, Yoon-Jae, 2012. "Nonparametric estimation and inference about the overlap of two distributions," Journal of Econometrics, Elsevier, vol. 171(1), pages 1-23.
    7. Anderson, Gordon & Farcomeni, Alessio & Pittau, Maria Grazia & Zelli, Roberto, 2016. "A new approach to measuring and studying the characteristics of class membership: Examining poverty, inequality and polarization in urban China," Journal of Econometrics, Elsevier, vol. 191(2), pages 348-359.
    8. Adina Titei, 2021. "The Life Expectancy and the Economic Conditions in Pandemic Context in EU," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 538-541, December.
    9. Chemeris, Anna & Liu, Yong & Ker, Alan P., 2022. "Insurance subsidies, climate change, and innovation: Implications for crop yield resiliency," Food Policy, Elsevier, vol. 108(C).

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