国家和国家以下各级婴儿死亡率的预测：分组时间序列法
Reconciling forecasts of infant mortality rates at national and sub-national levels: Grouped time-series methods
摘要：
死亡率往往按性别、州、教育、宗教或族裔等不同属性分列。预测国家和国家以下各级的死亡率在制定与国家和国家以下各级有关的社会政策方面发挥着重要作用。然而，国家以下各级的基本预测可能与国家一级的预测不一致。为了解决这个问题，我们从分组时间序列预测方法的角度考虑了协调死亡率预测的问题（Hyndman等人，2011年）。一个自下而上的方法和最佳组合方法被应用到生产点预测的婴儿死亡率，适当地聚集在不同层次的层次结构。我们扩展这两种方法，考虑通过自助程序的区间预测的和解。以澳大利亚地区婴儿死亡率为例，研究了独立预测方法和两种分组时间序列预测方法的一步到20步预测精度和区间预测精度。所提出的方法被证明是有用的调和点和区间预测的人口率在国家和国家以下各级，并将有利于政府的政策决定，在国家和国家以下各级的当前和未来的资源分配。
英文摘要：
Mortality rates are often disaggregated by different attributes, such as sex, state, education, religion or ethnicity. Forecasting mortality rates at the national and sub-national levels plays an important role in making social policies associated with the national and sub-national levels. However, base forecasts at the sub-national levels may not add up to the forecasts at the national level. To address this issue, we consider the problem of reconciling mortality rate forecasts from the viewpoint of grouped time-series forecasting methods (Hyndman et al., 2011). A bottom-up method and an optimal combination method are applied to produce point forecasts of infant mortality rates that are aggregated appropriately across the different levels of a hierarchy. We extend these two methods by considering the reconciliation of interval forecasts through a bootstrap procedure. Using the regional infant mortality rates in Australia, we investigate the one-step-ahead to 20-step-ahead point and interval forecast accuracies among the independent and these two grouped time-series forecasting methods. The proposed methods are shown to be useful for reconciling point and interval forecasts of demographic rates at the national and sub-national levels, and would be beneficial for government policy decisions regarding the allocations of current and future resources at both the national and sub-national levels.
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