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Correlated mortality risks of siblings in Kenya

Author

Listed:
  • Walter Rasugu Omariba

    (Statistics Canada)

  • Fernando Rajulton

    (University of Western Ontario)

  • Roderic Beaujot

    (Western University)

Abstract

Random-effect models have been useful in demonstrating how unobserved factors are related to infant or child death clustering. Another potential hypothesis is state dependence whereby the death of an older sibling affects the risk of death of a subsequent sibling. Probit regression models incorporating state dependence and unobserved heterogeneity are applied to the 1998 Demographic and Health Survey (DHS) data for Kenya. We find that mortality risks of adjacent siblings are dependent: a child whose preceding sibling died is 1.8 times more likely to die. After adjusting for unobserved heterogeneity, the death of the previous child accounts for 40% of child death clustering. Further, eliminating state dependence would reduce infant mortality among second- and higher-order births by 12.5%.

Suggested Citation

  • Walter Rasugu Omariba & Fernando Rajulton & Roderic Beaujot, 2008. "Correlated mortality risks of siblings in Kenya," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 18(11), pages 311-336, April.
  • Handle: RePEc:dem:demres:v:18:y:2008:i:11
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    File URL: https://www.demographic-research.org/volumes/vol18/11/18-11.pdf
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    References listed on IDEAS

    as
    1. Bhalotra, Sonia & Soest, Arthur van, 2008. "Birth-spacing, fertility and neonatal mortality in India: Dynamics, frailty, and fecundity," Journal of Econometrics, Elsevier, vol. 143(2), pages 274-290, April.
    2. Mark Montgomery & Paul Hewett, 2005. "Urban poverty and health in developing countries: Household and neighborhood Effects," Demography, Springer;Population Association of America (PAA), vol. 42(3), pages 397-425, August.
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    5. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    6. D. Omariba & Roderic Beaujot & Fernando Rajulton, 2007. "Determinants of infant and child mortality in Kenya: an analysis controlling for frailty effects," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(3), pages 299-321, June.
    7. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics,in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
    8. repec:aph:ajpbhl:1984:74:10:1098-1106_6 is not listed on IDEAS
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    Cited by:

    1. van Soest, A.H.O. & Saha, U.R., 2012. "Does Family Planning Reduce Infant Mortality? Evidence from Surveillance Data in Matlab, Bangladesh," Discussion Paper 2012-019, Tilburg University, Center for Economic Research.

    More about this item

    Keywords

    death clustering; initial conditions problem; Kenya; logit model; sequence data; state dependence; unobserved heterogeneity;

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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