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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.
  • Handle: RePEc:dem:demres:v:18:y:2008:i:11
    DOI: 10.4054/DemRes.2008.18.11
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    References 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.
    2. Saha, U.R. & van Soest, A.H.O., 2009. "Infant Mortality in Rural Bangladesh : State Dependence vs. Unobserved Heterogeneity," Discussion Paper 2009-26, Tilburg University, Center for Economic Research.
    3. van Soest, A.H.O. & Saha, U.R., 2012. "Birth Spacing, Child Survival and Fertility Decisions : Analysis of Causal Mechanismsa," Discussion Paper 2012-018, Tilburg University, Center for Economic Research.
    4. Mukesh Ranjan & Laxmi Kant Dwivedi & Shivalingappa Halli, 2022. "Infant Death Clustering in the Quarter of a Century in India: A Decomposition Analysis," IJERPH, MDPI, vol. 19(21), pages 1-21, November.

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    More about this item

    Keywords

    unobserved heterogeneity; Kenya; death clustering; initial conditions problem; sequence data; state dependence; logit model;
    All these keywords.

    JEL classification:

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

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