Forecasting cohort incomplete fertility: A method and an application.

Nan Li, Zheng Wu
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引用次数: 19

Abstract

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.

预测队列不完全生育:一种方法及应用。
借鉴前人对生育率预测的见解,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)模型来建立完整队列的生育水平与年龄模式之间的关系。然后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。除日本外,我们的结果表明,该模型与数据吻合得很好,加拿大、美国和挪威的总生育率可以可靠预测的最年轻队列是25岁。我们的方法不太适用于日本,在日本,总生育率可以预测的最年轻群体是35岁或以上。我们在模型假设的背景下讨论了我们的方法的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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