May 23, 2018

Measuring fertility through mobile‒phone based household surveys: Methods, data quality, and lessons learned from PMA2020 surveys

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Authors: Yoonjoung Choi, Qingfeng Li, & Blake Zachary

Journal: Demographic Research, 38(55). May 2018

This article documents methods and assesses the quality of fertility data in Performance Monitoring and Accountability 2020 (PMA2020) surveys, focusing on potential bias introduced from the type of birth history questions in the questionnaire and completeness and distribution of birth month and year input. Researchers simulated births that would be counted using the PMA2020 questionnaires compared to births identified from full birth history. The team also analyzed the latest Demographic and Health Surveys in ten countries where PMA2020 surveys have been implemented. The researchers found:

  • Simple questions introduced minor bias from undercounting multiple births, which was expected and had been corrected.
  • However, incomplete reporting of birth month was relatively high but had decreased. The default value of January for missing months in data collection software systematically moved births with missing months out of the reference period.
  • On average, across 39 surveys, total fertility rate (TFR) increased by 1.6% and 2.4%, adjusted for undercounted multiple births and heaping on January, respectively.