Department of Statistics and Applied Probability, National University of Singapore, Singapore.
Demography. 2011 Aug;48(3):815-39. doi: 10.1007/s13524-011-0040-5.
We describe a Bayesian projection model to produce country-specific projections of the total fertility rate (TFR) for all countries. The model decomposes the evolution of TFR into three phases: pre-transition high fertility, the fertility transition, and post-transition low fertility. The model for the fertility decline builds on the United Nations Population Division's current deterministic projection methodology, which assumes that fertility will eventually fall below replacement level. It models the decline in TFR as the sum of two logistic functions that depend on the current TFR level, and a random term. A Bayesian hierarchical model is used to project future TFR based on both the country's TFR history and the pattern of all countries. It is estimated from United Nations estimates of past TFR in all countries using a Markov chain Monte Carlo algorithm. The post-transition low fertility phase is modeled using an autoregressive model, in which long-term TFR projections converge toward and oscillate around replacement level. The method is evaluated using out-of-sample projections for the period since 1980 and the period since 1995, and is found to be well calibrated.
我们描述了一种贝叶斯投影模型,用于为所有国家生成特定国家的总生育率(TFR)预测。该模型将 TFR 的演变分解为三个阶段:前过渡时期的高生育率、生育率过渡时期和后过渡时期的低生育率。生育率下降的模型基于联合国人口司当前的确定性预测方法,该方法假设生育率最终将低于更替水平。它将 TFR 的下降建模为两个逻辑函数的总和,这两个逻辑函数取决于当前的 TFR 水平和一个随机项。贝叶斯层次模型用于根据国家的 TFR 历史和所有国家的模式来预测未来的 TFR。它是使用马尔可夫链蒙特卡罗算法根据所有国家过去的 TFR 联合国估计值进行估算的。后过渡时期的低生育率阶段使用自回归模型进行建模,其中长期 TFR 预测值收敛于更替水平并围绕更替水平波动。该方法使用 1980 年以来和 1995 年以来的样本外预测进行评估,结果表明该方法具有良好的校准效果。