Literature DB >> 34421446

Smoothing, Decomposing and Forecasting Mortality Rates.

Carlo G Camarda1, Ugofilippo Basellini1,2.   

Abstract

The Lee-Carter (LC) model represents a landmark paper in mortality forecasting. While having been widely accepted and adopted, the model has some limitations that hinder its performance. Some variants of the model have been proposed to deal with these drawbacks individually, none coped with them all at the same time. In this paper, we propose a Three-Component smooth Lee-Carter (3C-sLC) model which overcomes many of the issues simultaneously. It decomposes mortality development into childhood, early-adult and senescent mortality, which are described, individually, by a smooth variant of the LC model. Smoothness is enforced to avoid irregular patterns in projected life tables, and complexity in the forecasting methodology is unaltered with respect to the original LC model. Component-specific schedules are considered in projections, providing additional insights into mortality forecasts. We illustrate the proposed approach to mortality data for ten low-mortality populations. The 3C-sLC captures mortality developments better than a smooth improved version of the LC model, and it displays wider prediction intervals. The proposed approach provides actuaries, demographers, epidemiologists and social scientists in general with a unique and valuable tool to simultaneously smooth, decompose and forecast mortality.
© The Author(s), under exclusive licence to Springer Nature B.V. 2021.

Entities:  

Keywords:  Lee–Carter model; Mortality decomposition; Mortality forecasting; Rate of mortality improvement; Smoothness

Year:  2021        PMID: 34421446      PMCID: PMC8333270          DOI: 10.1007/s10680-021-09582-4

Source DB:  PubMed          Journal:  Eur J Popul        ISSN: 0168-6577


  28 in total

1.  Applying Lee-Carter under conditions of variable mortality decline.

Authors:  Heather Booth; John Maindonald; Len Smith
Journal:  Popul Stud (Camb)       Date:  2002-11

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Authors:  A Rogers; J S Little
Journal:  Math Popul Stud       Date:  1994-02       Impact factor: 0.720

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Authors:  Steven Haberman; Arthur Renshaw
Journal:  Lifetime Data Anal       Date:  2008-03-03       Impact factor: 1.588

4.  Switzerland, HIV and the power of pragmatism: lessons for drug policy development.

Authors:  Joanne Csete; Peter J Grob
Journal:  Int J Drug Policy       Date:  2011-08-17

5.  Optimizing the Lee-Carter Approach in the Presence of Structural Changes in Time and Age Patterns of Mortality Improvements.

Authors:  Hong Li; Johnny Siu-Hang Li
Journal:  Demography       Date:  2017-06

6.  A mortality model based on a mixture distribution function.

Authors:  Stefano Mazzuco; Bruno Scarpa; Lucia Zanotto
Journal:  Popul Stud (Camb)       Date:  2018-03-29

7.  Parameters of mortality in human populations with widely varying life spans.

Authors:  W Siler
Journal:  Stat Med       Date:  1983 Jul-Sep       Impact factor: 2.373

8.  The contribution of drug-related deaths to the US disadvantage in mortality.

Authors:  Magali Barbieri
Journal:  Int J Epidemiol       Date:  2019-06-01       Impact factor: 7.196

9.  A new parametric model to assess delay and compression of mortality.

Authors:  Joop de Beer; Fanny Janssen
Journal:  Popul Health Metr       Date:  2016-12-01

10.  Lifespan Disparity as an Additional Indicator for Evaluating Mortality Forecasts.

Authors:  Christina Bohk-Ewald; Marcus Ebeling; Roland Rau
Journal:  Demography       Date:  2017-08
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  1 in total

1.  How to measure premature mortality? A proposal combining "relative" and "absolute" approaches.

Authors:  Stefano Mazzuco; Marc Suhrcke; Lucia Zanotto
Journal:  Popul Health Metr       Date:  2021-10-26
  1 in total

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