Rabbi Ahbab Mohammad Fazle, Mazzuco Stefano
Department of Statistical Sciences, University of Padua, Padua, Italy.
Eur J Popul. 2020 Apr 8;37(1):97-120. doi: 10.1007/s10680-020-09559-9. eCollection 2021 Mar.
Reliable mortality forecasts are an essential component of healthcare policies in ageing societies. The Lee-Carter method and its later variants are widely accepted probabilistic approaches to mortality forecasting, due to their simplicity and the straightforward interpretation of the model parameters. This model assumes an invariant age component and linear time component for forecasting. We apply the Lee-Carter method on smoothed mortality rates obtained by LASSO-type regularization and hence adjust the time component with the observed lifespan disparity. Smoothing with LASSO produces less error during the fitting period than do spline-based smoothing techniques. As a more informative indicator of longevity, matching with lifespan disparity makes the time component more reflective of mortality improvements. The forecasts produced by the new method were more accurate during out-of-sample evaluation and provided optimistic forecasts for many low-mortality countries.
可靠的死亡率预测是老龄化社会医疗政策的重要组成部分。李-卡特方法及其后来的变体是广泛接受的死亡率预测概率方法,因为它们简单且模型参数易于解释。该模型假设预测时年龄成分不变且时间成分呈线性。我们将李-卡特方法应用于通过套索型正则化获得的平滑死亡率,从而根据观察到的寿命差异调整时间成分。与基于样条的平滑技术相比,套索平滑在拟合期产生的误差更小。作为更具信息量的长寿指标,与寿命差异相匹配使时间成分更能反映死亡率的改善情况。新方法产生的预测在样本外评估期间更准确,并且为许多低死亡率国家提供了乐观的预测。