a Max Planck Institute for Demographic Research.
Popul Stud (Camb). 2003 Nov;57(3):303-20. doi: 10.1080/0032472032000137826.
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.
借鉴先前关于生育率预测的研究成果，我们开发了一种预测不完全队列生育率的方法。我们的方法包括两个基本步骤。首先，我们使用奇异值分解（SVD）模型来建立完成队列生育率水平和年龄模式之间的关系。然后，我们将这种关系应用于不完全队列，以获得预测生育率。我们提出了评估模型假设的技术，并使用来自加拿大、美国、挪威和日本的队列数据来说明我们的方法。除了日本，我们的结果表明，该模型很好地拟合了数据，并且可以可靠预测生育率的最年轻队列的年龄为 25 岁，适用于加拿大、美国和挪威。我们的方法在模型假设的背景下对日本的适用性较低，在日本，最年轻队列的总生育率可以预测的年龄为 35 岁或以上。我们讨论了我们的方法在模型假设下的局限性。
