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Two‐Dimensional Kernel Smoothing of Mortality Surface: An Evaluation of Cohort Strength
Author(s) -
Li Han,
O'hare Colin,
Vahid Farshid
Publication year - 2016
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.2399
Subject(s) - life expectancy , cohort , econometrics , smoothing , mortality rate , kernel density estimation , bivariate analysis , cohort effect , actuarial science , statistics , credit score , computer science , medicine , economics , mathematics , population , environmental health , estimator
Accurate mortality forecasts are of primary interest to insurance companies, pension providers and government welfare systems owing to the rapid increase in life expectancy during the past few decades. Existing mortality models in the literature tend to project future mortality rates by extracting the observed patterns in the mortality surface. Patterns found in the cohort dimension have received a considerable amount of attention and are included in many models of mortality. However, to our knowledge very few studies have considered an evaluation and comparison of cohort patterns across different countries. Moreover, the answer to the question of how the incorporation of the cohort effect affects the forecasting performance of mortality models still remains unclear. In this paper we introduce a new way of incorporating the cohort effect at the beginning of the estimation stage via the implementation of kernel smoothing techniques. Bivariate standard normal kernel density is used and we capture the cohort effect by assigning greater weights along the diagonals of the mortality surface. Based on the results from our empirical study, we compare and discuss the differences in cohort strength across a range of developed countries. Further, the fitting and forecasting results demonstrate the superior performance of our model when compared to some well‐known mortality models in the literature under a majority of circumstances. Copyright © 2016 John Wiley & Sons, Ltd.

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