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On the contribution of demographic change to aggregate poverty measures for the developing world

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  • Ravallion, Martin

Abstract

Recent literature and new data help determine plausible bounds to some key demographic differences between the poor and non-poor in the developing world. The author estimates that selective mortality-whereby poorer people tend to have higher death rates-accounts for 10-30 percent of the developing world's trend rate of"$1 a day"poverty reduction in the 1990s. However, in a neighborhood of plausible estimates, differential fertility-whereby poorer people tend also to have higher birth rates-has had a more than offsetting poverty-increasing effect. The net impact of differential natural population growth represents 10-50 percent of the trend rate of poverty reduction.

Suggested Citation

  • Ravallion, Martin, 2005. "On the contribution of demographic change to aggregate poverty measures for the developing world," Policy Research Working Paper Series 3580, The World Bank.
    • Handle: RePEc:wbk:wbrwps:3580
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    References listed on IDEAS

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    1. T. Paul Schultz, 2004. "Demographic Determinants of Savings: Estimating and Interpreting the Aggregate Association in Asia," Working Papers 901, Economic Growth Center, Yale University.
    2. Gaurav Datt & Martin Ravallion, 1998. "Farm productivity and rural poverty in India," Journal of Development Studies, Taylor & Francis Journals, vol. 34(4), pages 62-85.
    3. Ainsworth, Martha & Filmer, Deon, 2002. "Poverty, AIDS, and children's schooling - a targeting dilemma," Policy Research Working Paper Series 2885, The World Bank.
    4. Ravi Kanbur & Diganta Mukherjee, 2007. "Premature Mortality And Poverty Measurement," Bulletin of Economic Research, Wiley Blackwell, vol. 59(4), pages 339-359, October.
    5. Lanjouw, Peter & Ravallion, Martin, 1995. "Poverty and Household Size," Economic Journal, Royal Economic Society, vol. 105(433), pages 1415-1434, November.
    6. de Walque, Damien, 2007. "How does the impact of an HIV/AIDS information campaign vary with educational attainment? Evidence from rural Uganda," Journal of Development Economics, Elsevier, vol. 84(2), pages 686-714, November.
    7. Bidani, Benu & Ravallion, Martin, 1997. "Decomposing social indicators using distributional data," Journal of Econometrics, Elsevier, vol. 77(1), pages 125-139, March.
    8. repec:aph:ajpbhl:1995:85:7:949-956_1 is not listed on IDEAS
    9. Xavier Sala-I-Martin & Gernot Doppelhofer & Ronald I. Miller, 2004. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," American Economic Review, American Economic Association, vol. 94(4), pages 813-835, September.
    10. Deon Filmer & Lant Pritchett, 1999. "The Effect of Household Wealth on Educational Attainment: Evidence from 35 Countries," Population and Development Review, The Population Council, Inc., vol. 25(1), pages 85-120.
    11. Eastwood, Robert & Lipton, Michael, 1997. "The impact of changes in human fertility on poverty," Discussion Papers in Economics 01/97, Department of Economics, University of Sussex Business School.
    12. Robert Eastwood & Michael Lipton, 1999. "The impact of changes in human fertility on poverty," Journal of Development Studies, Taylor & Francis Journals, vol. 36(1), pages 1-30.
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    Cited by:

    1. Michael Grimm & Kenneth Harttgen, 2008. "Longer life, higher welfare?," Oxford Economic Papers, Oxford University Press, vol. 60(2), pages 193-211, April.
    2. Kenneth Harttgen, 2007. "The Impact of HIV on Children´s Welfare," Ibero America Institute for Econ. Research (IAI) Discussion Papers 157, Ibero-America Institute for Economic Research.

    More about this item

    Keywords

    Health Monitoring&Evaluation; Services&Transfers to Poor; Safety Nets and Transfers; Rural Poverty Reduction; Health Indicators;

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