In this project, we first propose a multi-dimensional Bühlmann credibility approach to forecasting mortality rates for multiple populations, and then compare forecasting performances among the proposed approach and the joint-k/co-integrated/augmented common factor Lee-Carter models. The model is applied to mortality data of the Human Mortality Database for both genders of three well-developed countries with an age span and a wide range of fitting year spans. Empirical illustrations show that the proposed multi-dimensional Bühlmann credibility approach contributes to more accurate forecast results, measured by MAPE (mean absolute percentage error), than those based on the Lee-Carter model.
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