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Are sibling models a suitable tool in analyses of how reproductive factors affect child mortality?

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  • Øystein Kravdal

    (Universitetet i Oslo)

Abstract

Background: Several studies of how reproductive factors affect child mortality or other child outcomes have been based on sibling comparisons. With such models one controls for unobserved determinants of the outcome that are shared by the siblings and linked to the reproductive process. However, it has been shown mathematically that estimates from sibling models are biased when the outcome for one sibling affects the exposure for another, and this is precisely the situation when the outcome is child mortality and the exposure is aspects of the mother’s reproductive behaviour. The goal of this analysis was to find out, by means of simulation, whether the bias really matters in practice. Results: All simulation experiments showed that, when there was an effect of infant mortality on subsequent fertility, the estimated effect of higher maternal age was considerably more adverse than the true effect, while the effects of higher birth order and very short or very long birth interval were biased in the opposite direction. Contribution: Although it is possible that the bias is unimportant in other situations than those examined here, a reasonable conclusion is that one should have serious doubts about sibling model estimates of effects of reproductive factors on infant or child mortality. Stated differently, we may know less about these effects than we tend to think and need other alternatives to a ‘naïve’ regression model than the sibling approach. Obviously, there may be problems also when analysing other child outcomes that affect subsequent fertility, through mortality or otherwise.

Suggested Citation

  • Øystein Kravdal, 2020. "Are sibling models a suitable tool in analyses of how reproductive factors affect child mortality?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(28), pages 777-798.
  • Handle: RePEc:dem:demres:v:42:y:2020:i:28
    DOI: 10.4054/DemRes.2020.42.28
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    References listed on IDEAS

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    1. Joseph Molitoris & Kieron Barclay & Martin Kolk, 2019. "When and Where Birth Spacing Matters for Child Survival: An International Comparison Using the DHS," Demography, Springer;Population Association of America (PAA), vol. 56(4), pages 1349-1370, August.
    2. Kieron J. Barclay & Martin Kolk, 2017. "The Long-Term Cognitive and Socioeconomic Consequences of Birth Intervals: A Within-Family Sibling Comparison Using Swedish Register Data," Demography, Springer;Population Association of America (PAA), vol. 54(2), pages 459-484, April.
    3. Øystein Kravdal, 2018. "New evidence about effects of reproductive variables on child mortality in sub-Saharan Africa," Population Studies, Taylor & Francis Journals, vol. 72(2), pages 139-156, May.
    4. Kieron Barclay & Mikko Myrskylä, 2016. "Advanced Maternal Age and Offspring Outcomes: Reproductive Aging and Counterbalancing Period Trends," Population and Development Review, The Population Council, Inc., vol. 42(1), pages 69-94, March.
    5. Øystein Kravdal, 2019. "Taking birth year into account when analysing effects of maternal age on child health and other outcomes: The value of a multilevel-multiprocess model compared to a sibling model," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(43), pages 1249-1290.
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    Cited by:

    1. Kieron J. Barclay & Ken R. Smith, 2020. "The effects of birth spacing on health and socioeconomic outcomes across the life course: evidence from the Utah Population Database," MPIDR Working Papers WP-2020-038, Max Planck Institute for Demographic Research, Rostock, Germany.

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    More about this item

    Keywords

    bias; child mortality; sibling models; reproductive factors;
    All these keywords.

    JEL classification:

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

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