Probabilistic projections of the total fertility rate
Leontine Alkema, National University of Singapore
Adrian Raftery, University of Washington
Patrick Gerland, United Nations Population Division
Samuel J. Clark, University of Washington
François Pelletier, United Nations Population Division
We developed a methodology to construct probabilistic projections of the total fertility rate (TFR) that could be applied to all countries in the world for which the fertility is currently above replacement level. Our methodology builds onto the one currently used by the United Nations Population Division, which assumes that fertility will eventually fall below replacement level. We propose a time series model for deriving country-specific projections, in which the pace of the fertility decline is decomposed into a systematic decline with distortion terms added to it. The pace of the systematic decline in the TFR is modeled as a function of its level, based on the UN methodology. We propose a Bayesian hierarchical model to estimate the parameters of the decline function. The projected TFRs and the corresponding prediction intervals will shed new light on future population dynamics, including on dependency ratios and on the pace of population ageing.