Forecasting cohort incomplete fertility: A method and an application.

Drawing on insights from previous work on fertility forecasts, we develop a method for forecasting incomplete cohort fertility. Our approach involves two basic steps. First, we use a singular-value-decomposition (SVD) model to establish a relationship between the level and the age pattern of fertility for completed cohorts. This relationship is then applied to incomplete cohorts to obtain forecast fertility. We propose techniques to evaluate model assumptions and illustrate our method using cohort data from Canada, the USA, Norway, and Japan. With the exception of Japan, our results show that the model fits the data well, and that the youngest cohort whose total fertility can be reliably forecast is age 25 for Canada, the USA, and Norway. Our method is less applicable to Japan, where the youngest cohort whose total fertility could be forecast was age 35 or older. We discuss the limitations of our method in the context of model assumptions.