Abstract
BackgroundAn adequate forecasting model of mortality that allows an analysis of different population changes is a topic of interest for countries in demographic transition. Phenomena such as the reduction of mortality, ageing, and the increase in life expectancy are extremely useful in the planning of public policies that seek to promote the economic and social development of countries. To our knowledge, this paper is one of the first to evaluate the performance of mortality forecasting models applied to abridged life tables.ObjectiveSelect a mortality model that best describes and forecasts the characteristics of mortality in Colombia when only abridged life tables are available.Data and methodWe used Colombian abridged life tables for the period 1973–2005 with data from the Latin American Human Mortality Database. Different mortality models to deal with modeling and forecasting probability of death are presented in this study. For the comparison of mortality models, two criteria were analyzed: graphical residuals analysis and the hold-out method to evaluate the predictive performance of the models, applying different goodness of fit measures.ResultsOnly three models did not have convergence problems: Lee-Carter (LC), Lee-Carter with two terms (LC2), and Age-Period-Cohort (APC) models. All models fit better for women, the improvement of LC2 on LC is mostly for central ages for men, and the APC model’s fit is worse than the other two. The analysis of the standardized deviance residuals allows us to deduce that the models that reasonably fit the Colombian mortality data are LC and LC2. The major residuals correspond to children’s ages and later ages for both sexes.ConclusionThe LC and LC2 models present better goodness of fit, identifying the principal characteristics of mortality for Colombia.Mortality forecasting from abridged life tables by sex has clear added value for studying differences between developing countries and convergence/divergence of demographic changes.
Highlights
The study of mortality and its characteristics and forecasting allow us to understand population dynamics and their tendencies
The analysis of the standardized deviance residuals allows us to deduce that the models that reasonably fit the Colombian mortality data are LC and Lee-Carter with two terms (LC2)
Estimation of mortality from a good forecasting model is important considering the impact that its results have on the different processes of social and economic planning of a country
Summary
The study of mortality and its characteristics and forecasting allow us to understand population dynamics and their tendencies Phenomena such as population growth and the reduction of mortality are of great interest given the economic and social impact they have on the development of countries. An adequate forecasting model of mortality that allows an analysis of different population changes is a topic of interest for countries in demographic transition. Phenomena such as the reduction of mortality, ageing, and the increase in life expectancy are extremely useful in the planning of public policies that seek to promote the economic and social development of countries. This paper is one of the first to evaluate the performance of mortality forecasting models applied to abridged life tables
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