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Accumulating Birth Histories Across Surveys for Improved Estimates of Child Mortality

Author

Listed:
  • Laura Schmidt

    (Goethe University)

  • Mahmoud Elkasabi

    (The DHS Program, ICF)

Abstract

Producing reliable estimates for childhood mortality rates is essential to monitor progress towards the United Nations Sustainable Development Goals (UN SDGs) and correctly evaluate policies designed to reduce childhood mortality rates. Different model-based approaches have been proposed to assess levels and trends in childhood mortality indicators. In this paper, we propose a design-based complement that accumulates birth histories across different household surveys to increase the precision of childhood mortality rates estimates. We accumulate birth histories across different cross-sectional Demographic Health Surveys/Multiple Cluster Indicator Surveys collected in Senegal and Malawi and estimate pooled childhood mortality rates based on calendar years. We show that accumulating birth histories smoothens fluctuations in time series for national and sub-national mortality rates, establishes more stable and reliable time trends, and results in estimated standard errors of the cumulated rates that are about 50–60% lower than their counterparts from separate surveys.

Suggested Citation

  • Laura Schmidt & Mahmoud Elkasabi, 2022. "Accumulating Birth Histories Across Surveys for Improved Estimates of Child Mortality," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(5), pages 2177-2209, October.
    • Handle: RePEc:kap:poprpr:v:41:y:2022:i:5:d:10.1007_s11113-022-09721-7
    DOI: 10.1007/s11113-022-09721-7
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    References listed on IDEAS

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    1. Mahmoud A. Elkasabi & Steven G. Heeringa & James M. Lepkowski, 2015. "Joint Calibration Estimator For Dual Frame Surveys," Statistics in Transition New Series, Polish Statistical Association, vol. 16(1), pages 7-36, March.
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    4. Monica Alexander & Leontine Alkema, 2018. "Global estimation of neonatal mortality using a Bayesian hierarchical splines regression model," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 38(15), pages 335-372.
    5. Jon Pedersen & Jing Liu, 2012. "Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories," PLOS Medicine, Public Library of Science, vol. 9(8), pages 1-13, August.
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