Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/312325 
Year of Publication: 
2022
Citation: 
[Journal:] Population Research and Policy Review [ISSN:] 1573-7829 [Volume:] 41 [Issue:] 5 [Publisher:] Springer Netherlands [Place:] Dordrecht [Year:] 2022 [Pages:] 2177-2209
Publisher: 
Springer Netherlands, Dordrecht
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.
Subjects: 
Childhood mortality rates
Under-5 mortality rate
Cumulating survey data
DHS surveys
MICS surveys
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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