Prediction of China’s Population Mortality under Limited Data

Abstract

Population mortality is an important step in quantifying the risk of longevity. China lacks data on population mortality, especially the elderly population. Therefore, this paper first uses spline fitting to supplement the missing data and then uses dynamic models to predict the species mortality of the Chinese population, including age extrapolation and trend extrapolation. Firstly, for age extrapolation, kannisto is used to expand the data of the high-age population. Secondly, the Lee-Carter single-factor model is used to predict gender and age mortality. This paper fills and smoothes the deficiencies of the original data to make up for the deficiencies of our population mortality data and improve the prediction accuracy of population mortality and life expectancy, while analyzing the impact of mortality improvement and providing a theoretical basis for policies to deal with the risk of longevity.