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Mortality forecasting and trend shifts: an application of the Lee-Carter model to Swedish mortality data. (English) Zbl 1330.62437
Summary: We examine how the Lee-Carter model fares with Swedish data for the period 1901-2001 and for segments of this period. We have choosen to censor ages less than age 40 as those ages only are of marginal interest to the forecast. At age 40 some 98 to 99 percent of the birth cohorts are survivors. In the study we only consider the unweighted K1 estimates. The Lee-Carter model provides very good fits to the data. When splitting up the base period there seems to be an interaction beween the age and time components of the model. In order to deal with the different phases of falling mortality for males and females possibly one should choose the past 25 years as a base in the model. Selecting the base period is however a judgmental issue depending on the main focus of the forecast. Is it long-term, short-term or, as in Sweden, a combination of both?

MSC:
62P25 Applications of statistics to social sciences
62M20 Inference from stochastic processes and prediction
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
91D20 Mathematical geography and demography
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References:
[1] Booth, Age-time interactions in mortality projection: Applying Lee-Carter to Australia (2002)
[2] Carter, Examining Structural Shifts in Mortality Using the Lee-Carter Method (2001)
[3] Good, Some Applications of the Singular Decomposition of a Matrix., Technometrics 11 (4) pp 823– (1969) · Zbl 0186.33803
[4] Lee, Modeling and Forecasting U.S. Mortality., J. Amer. Statist. Assoc. 87 (419) pp 659– (1992)
[5] Wilmoth, Computational Methods for Fitting and Extrapolating the Lee-Carter Model of Mortality Change (1993)
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