A flexible model to reconstruct education-specific fertility rates: Sub-Saharan Africa case

The future world population growth and size will be largely determined by the pace of fertility decline in sub-Saharan Africa. Correct estimates of education-specific fertility rates are crucial for projecting the future population. Yet, consistent crosscountry, comparable estimates of education-specific fertility for sub-Saharan African countries are still lacking. We propose a flexible Bayesian hierarchical model that reconstructs education-specific fertility rates by combining the patchy Demographic and Health Surveys (DHS) data and the United Nations’ (UN) reliable estimates of total fertility rates (TFR). Our model produces estimates that match the UN TFR to different extents (in other words, estimates of varying levels of consistency with the UN). We present three model specifications: Consistent but not identical with the UN; fully-consistent (nearly identical) with the UN, and consistent with the DHS. Further, we provide a full time series of education-specific TFR estimates covering five-year periods between 1980 and 2014 for 36 sub-Saharan African countries. The results show that the DHS-consistent estimates are usually higher than the UN-fully-consistent ones. The differences between the three model estimates vary substantially in size across countries, yielding 1980–2014 fertility trends that diverge from each other—mostly in level only, but also sometimes in direction.