A flexible model for reconstructing education-specific fertility rates: The case of sub-Saharan Africa

BACKGROUNDAccurate and harmonized estimates of education-specific fertility rates are crucial for understanding the past and projecting the future human population.Yet fertility estimates derived from demographic surveys that collect detailed fertility histories often do not align with the reliable and widely used United Nations (UN) World Population Prospects.This inconsistency means that the choice of data source can affect research outcomes on fertility trends. OBJECTIVEWe combine the patchy Demographic and Health Surveys (DHS) data and the UN total fertility rate (TFR) estimates to create three harmonized datasets of education-specific TFRs for 36 sub-Saharan African countries, with different degrees of consistency with the UN TFR. METHODSWe develop a flexible Bayesian hierarchical model that reconstructs education-specific fertility rates by combining the DHS data and the UN TFR estimates.