Mortality Forecasting For China Based On The Long-run Equilibrium Relations

With the promotion of human health awareness,the desire for longevity also increased.Subjectively,human beings pay more attention to fitness,and develop a variety of healthy habit.Objectively,the substantial increase of the medical level has also given people a great protection.Human life gradually began to be extended,but it also brought longevity risk and many other issues.Government,enterprises,pension agencies and individuals would suffer more economic pressure because of the longevity risk.It has become the focus of attention that how to measure longevity risk.The demographic mortality rate reflects the overall strength of the various aspects of the country,and accurate predictions can lay an important data base for the measurement of longevity risk.It can guide all organizations to take timely measures to respond to future longevity risks better.Considering the imperfection,non-normality and limitedness of population data in China,this paper combined with the mortality of China mainland and Taiwan province.Based on the classical Lee-Carter model,the paper built a prediction model for mortality prediction.The least squares method was used to estimate three parameters in the model.Considering the correlation of the death rate fitting residuals,The VECM model was established to predict the death rate series.Before the prediction,the paper did cointergration analysis to find out the long-run equilibrium of mortality rates between China mainland and Taiwan province,and the VECM(1)model was obtained after the cointegration test.Finally,based on this correlation,the predicted value of China's future population mortality rate from 2011 to 2022 was obtained.In order to verify the influence of this correlation on the mortality prediction effect,this paper establishes a traditional model that does not consider the correlation,and compares the prediction results with the predictive results of the model.The ARIMA model for Chinese male is ARIMA model with ARIMA(1,1,0)with drifting,and ARIMA model suitable for Chinese women is ARIMA(0,1,0)with drift items.Using the 1994-2010 mortality rate of the original data as a training set,the 2011-2020 population mortality forecast results.The validity of the model is validated by the comparison of the two predictions.In this paper,the real data of the mortality rate from 2011 to 2013 is used as the test set of the model to predict the effect.The mean square error is used as the test standard.The results show that in terms of year change and gender,the predictive results of correlation are far better than those based on the traditional model,which do not consider the correlation to the mortality rate.Considering the correlation of the mortality prediction model can effectively compensate for the shortcomings of China's mortality data,can make the forecast more accurate.This correlationcan also be used for longevity risk measurement,which is used as the data base for the pricing of longevity risk bonds in both regions.The impact of longevity risk on China's future will be more and more,so based on this model to improve the model of mortality prediction results can be used to further production of life table for the late longevity risk to lay the foundation for deep discussion.