A Bayesian Model for the Reconstruction of Education- and Age-Specific Fertility Rates: An Application to African and Latin American Countries

Afua Durowaa-Boateng, Vienna Institute of Demography
Dilek Yildiz, International Institute for Applied Systems Analysis
Anne Goujon, International Institute for Applied Systems Analysis (IIASA)

Consistent and reliable past time series of education- and age-specific fertility rates are difficult to obtain in developing countries, although they are needed to evaluate the impact of women’s education on fertility along periods and cohorts. We aim to fill the existing gap by reconstructing age-specific fertility rates by level of education for African and Latin American countries from 1970 to 2020 in five-year steps. We developed a Bayesian framework to reconstruct age-specific fertility rates by level of education using prior information from the birth history of the Demographic and Health Surveys (DHS). From a methodological point of view, we show that the Bayesian reconstruction model allows for estimating missing data on fertility by levels of educational attainment. This information will be key to account for the role of education on fertility rates and assess the impacts of education policies in countries in Africa and Latin America.