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The Properties of the Watts Poverty Index under Lognormality

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  • Christophe Muller

    ()
    (University of Nottingham)

Abstract

Under lognormality assumption, we derive the parametric formula of the Watts measure, one of the main axiomatically sound poverty measures. In these conditions, we derive new properties of the Watts measure, its sensitivity to distribution parameters and its parametric standard error.

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File URL: http://www.accessecon.com/pubs/EB/2001/Volume9/EB-01I30001A.pdf
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Bibliographic Info

Article provided by AccessEcon in its journal Economics Bulletin.

Volume (Year): 9 (2001)
Issue (Month): 1 ()
Pages: 1-9

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Handle: RePEc:ebl:ecbull:eb-01i30001

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Keywords: Income Distribution;

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References

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  1. Maasoumi, Esfandiar, 1989. "Continuously distributed attributes and measures of multivariate inequality," Journal of Econometrics, Elsevier, vol. 42(1), pages 131-144, September.
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  14. Slesnick, Daniel T, 1993. "Gaining Ground: Poverty in the Postwar United States," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 1-38, February.
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  17. Majumder, Amita & Chakravarty, Satya Ranjan, 1990. "Distribution of Personal Income: Development of a New Model and Its Application to U.S. Income Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(2), pages 189-96, April-Jun.
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Citations

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Cited by:
  1. Christophe Muller, 2006. "Defining Poverty Lines As a Fraction of Central Tendency," Southern Economic Journal, Southern Economic Association, vol. 72(3), pages 720-729, January.
  2. Christophe Muller, 2005. "Poverty and inequality under income and price dispersions," Canadian Journal of Economics, Canadian Economics Association, vol. 38(3), pages 979-998, August.
  3. Christophe Muller, 2006. "Poverty Simulation And Price Changes," Working Papers. Serie AD 2006-13, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  4. Hajargasht, Gholamreza & Griffiths, William E., 2013. "Pareto–lognormal distributions: Inequality, poverty, and estimation from grouped income data," Economic Modelling, Elsevier, vol. 33(C), pages 593-604.

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