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FGT Poverty Measures and the Mortality Paradox: Theory and Evidence

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  • Mathieu Lefebvre

    (Université de Liège - Université de Liège)

  • Pierre Pestieau

    (PSE - Paris-Jourdan Sciences Economiques - CNRS : UMR8545 - École des Hautes Études en Sciences Sociales (EHESS) - École des Ponts ParisTech (ENPC) - École normale supérieure [ENS] - Paris - Institut national de la recherche agronomique (INRA), EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris, CORE - Center of Operation Research and Econometrics [Louvain] - Université Catholique de Louvain (UCL) - Belgique, CEPR - Center for Economic Policy Research - CEPR)

  • Grégory Ponthière

    (PSE - Paris-Jourdan Sciences Economiques - CNRS : UMR8545 - École des Hautes Études en Sciences Sociales (EHESS) - École des Ponts ParisTech (ENPC) - École normale supérieure [ENS] - Paris - Institut national de la recherche agronomique (INRA), EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

Abstract

Income-differentiated mortality, by reducing the share of poor persons in the population, leads to what can be called the "Mortality Paradox": the worse the survival conditions of the poor are, the lower the measured poverty is. We show that the extent to which FGT measures (Foster Greer Thorbecke 1984) underestimate old-age poverty under income-differentiated mortality depends on whether the prematurely dead would have, in case of survival, suffered from a more severe poverty than the average surviving population. Taking adjusted FGT measures with extended lifetime income profiles as a benchmark, we identify conditions under which the selection bias induced by income-differentiated mortality is higher for distribution-sensitive measures than for headcount measures. Finally, we show, on the basis of data on poverty in 11 European economies, that the size of the selection bias varies across different subclasses of FGT measures and across countries.

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Paper provided by HAL in its series PSE Working Papers with number halshs-00845490.

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Date of creation: Jul 2013
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Handle: RePEc:hal:psewpa:halshs-00845490

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Keywords: Income-differentiated mortality ; FGT poverty measures;

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  1. Ravi Kanbur & Diganta Mukherji, 2006. "Premature Mortality and Poverty Measurement," Working Papers id:707, eSocialSciences.
  2. Deaton, A., 2001. "Health, Inequality, and Economic Development," Papers 200, Princeton, Woodrow Wilson School - Development Studies.
  3. LEFEBVRE, Mathieu & PESTIEAU, Pierre & PONTHIERE, Grégory, 2011. "Measuring poverty without the mortality paradox," CORE Discussion Papers 2011068, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  4. John S. Greenlees & James E. Duggan & Robert Gillingham, 2007. "Mortality and Lifetime Income," IMF Working Papers 07/15, International Monetary Fund.
  5. Jusot, Florence, 2004. "Mortalité et revenu en France : construction et résultats d’une enquête cas-témoins," Economics Papers from University Paris Dauphine 123456789/451, Paris Dauphine University.
  6. Sen, Amartya, 1998. "Mortality as an Indicator of Economic Success and Failure," Economic Journal, Royal Economic Society, vol. 108(446), pages 1-25, January.
  7. Backlund, Eric & Sorlie, Paul D. & Johnson, Norman J., 1999. "A comparison of the relationships of education and income with mortality: the national longitudinal mortality study," Social Science & Medicine, Elsevier, vol. 49(10), pages 1373-1384, November.
  8. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-66, May.
  9. Harriet Orcutt Duleep, 1986. "Measuring the Effect of Income on Adult Mortality Using Longitudinal Administrative Record Data," Journal of Human Resources, University of Wisconsin Press, vol. 21(2), pages 238-251.
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