Historical Evolution of Old-Age Mortality and New Approaches to Mortality Forecasting.

Living to 100 monograph Pub Date : 2017-01-01 Epub Date: 2017-07-27
Leonid A Gavrilov, Natalia S Gavrilova, Vyacheslav N Krut'ko
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Abstract

Knowledge of future mortality levels and trends is important for actuarial practice but poses a challenge to actuaries and demographers. The Lee-Carter method, currently used for mortality forecasting, is based on the assumption that the historical evolution of mortality at all age groups is driven by one factor only. This approach cannot capture an additive manner of mortality decline observed before the 1960s. To overcome the limitation of the one-factor model of mortality and to determine the true number of factors underlying mortality changes over time, we suggest a new approach to mortality analysis and forecasting based on the method of latent variable analysis. The basic assumption of this approach is that most variation in mortality rates over time is a manifestation of a small number of latent variables, variation in which gives rise to the observed mortality patterns. To extract major components of mortality variation, we apply factor analysis to mortality changes in developed countries over the period of 1900-2014. Factor analysis of time series of age-specific death rates in 12 developed countries (data taken from the Human Mortality Database) identified two factors capable of explaining almost 94 to 99 percent of the variance in the temporal changes of adult death rates at ages 25 to 85 years. Analysis of these two factors reveals that the first factor is a "young-age" or background factor with high factor loadings at ages 30 to 45 years. The second factor can be called an "oldage" or senescent factor because of high factor loadings at ages 65 to 85 years. It was found that the senescent factor was relatively stable in the past but now is rapidly declining for both men and women. The decline of the senescent factor is faster for men, although in most countries, it started almost 30 years later. Factor analysis of time series of age-specific death rates conducted for the oldest-old ages (65 to 100 years) found two factors explaining variation of mortality at extremely old ages in the United States. The first factor is comparable to the senescent factor found for adult mortality. The second factor, however, is specific to extreme old ages (96 to 100 years) and shows peaks in 1960 and 2000. Although mortality below 90 to 95 years shows a steady decline with time driven by the senescent factor, mortality of centenarians does not decline and remains relatively stable. The approach suggested in this paper has several advantages. First, it is able to determine the total number of independent factors affecting mortality changes over time. Second, this approach allows researchers to determine the time interval in which underlying factors remain stable or undergo rapid changes. Most methods of mortality projections are not able to identify the best base period for mortality projections, attempting to use the longest-possible time period instead. We observe that the senescent factor of mortality continues to decline, and this decline does not demonstrate any indications of slowing down. At the same time, mortality of centenarians does not decline and remains stable. The lack of mortality decline at extremely old ages may diminish anticipated longevity gains in the future.

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老年死亡率的历史演变和死亡率预测的新方法。
对未来死亡率水平和趋势的了解对精算实践非常重要,但对精算师和人口学家也是一个挑战。目前用于预测死亡率的 Lee-Carter 方法所依据的假设是,所有年龄组死亡率的历史演变仅由一个因素驱动。这种方法无法捕捉到 20 世纪 60 年代之前观察到的死亡率下降的叠加方式。为了克服死亡率单因素模型的局限性,并确定死亡率随时间变化的真正因素数量,我们提出了一种基于潜在变量分析方法的死亡率分析和预测新方法。这种方法的基本假设是,死亡率随时间的变化大多是少数潜在变量的表现,这些变量的变化导致了观察到的死亡率模式。为了提取死亡率变化的主要成分,我们对发达国家 1900-2014 年期间的死亡率变化进行了因子分析。对 12 个发达国家特定年龄死亡率的时间序列(数据来自人类死亡率数据库)进行因子分析后发现,有两个因子能够解释 25 至 85 岁成人死亡率时间变化中近 94% 至 99% 的差异。对这两个因子的分析表明,第一个因子是 "青年 "或背景因子,在 30 至 45 岁时具有较高的因子负荷。第二个因子可称为 "老年 "或衰老因子,因为其在 65 至 85 岁时的因子载荷较高。研究发现,衰老因子在过去相对稳定,但现在无论男女都在迅速下降。男性衰老因子的下降速度更快,尽管在大多数国家,衰老因子的下降几乎是在 30 年后才开始的。对最老年龄段(65 至 100 岁)特定年龄死亡率的时间序列进行因子分析后发现,有两个因子可以解释美国极高龄死亡率的变化。第一个因素与成人死亡率中的衰老因素相似。然而,第二个因素是针对极高龄(96 至 100 岁)的,并在 1960 年和 2000 年达到高峰。虽然 90 至 95 岁以下的死亡率在衰老因子的作用下随着时间的推移稳步下降,但百岁老人的死亡率并没有下降,而是保持相对稳定。本文提出的方法有几个优点。首先,它能够确定影响死亡率随时间变化的独立因素的总数。其次,这种方法允许研究人员确定基本因素保持稳定或发生快速变化的时间间隔。大多数死亡率预测方法无法确定死亡率预测的最佳基期,而是试图使用可能的最长时间段。我们注意到,死亡率的衰老因素在继续下降,而且这种下降没有任何放缓的迹象。与此同时,百岁老人的死亡率并没有下降,而是保持稳定。极高龄人群的死亡率没有下降可能会降低未来预期的长寿收益。
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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