Modeling the Age Pattern of Fertility: An Individual-Level Approach

Macro-level modeling remains the dominant approach in many demographic applications, including population projections. Individual-level models tend to require larger amounts of data and very often cannot be estimated. The approach we introduce in this article attempts to overcome these limitations. Using likelihood-free inference techniques, we show that it is possible to infer the parameters of an individual-level model of the reproductive process from a set of aggregate fertility rates. By estimating individual-level quantities from widely available aggregate data, this approach can contribute to a better understanding of reproductive behavior and its driving mechanisms. It also allows for a more direct link between individual-level and population-level processes. We illustrate our approach using data from three natural fertility populations. The models we introduce can be readily applied in biodemography, to study the reproductive process in non-human populations