Flexible empirical Bayes estimation of local fertility schedules: reducing small area problems and preserving regional variation

Abstract

Reliable local demographic schedules are in high demand, but small area problems pose a challenge to estimation. The literature has directed little attention to the opportunities created by increased availability of high-quality geo-coded data. We propose the use of empirical Bayes methods based on a model with three hierarchical geographic levels to predict small area fertility schedules. The proposed model has a flexible specification with respect to age, which allows for detailed age heterogeneity in local fertility patterns. The model limits sampling variability in small areas, captures regional variations effectively, is robust to certain types of model misspecification, and outperforms alternative models in terms of prediction accuracy. The beneficial properties of the model are demonstrated through simulations and estimations on full-count Norwegian population data.