The Estimation Of Prospective Scale Of China’s Implicit Pension Debt

Social endowment insurance influences social stability and national economy. It is a multi-disciplinary involves sociology, economics and actuarial science. In order to response negative effects coursed by aging of population, in1997, China’s pension system was changed from " pay as you go system" to " pay as you go system" and "accumulation pension system". Changing of pension system caused IPD problem, which is the biggest problem to restrict the development of China’s pension system. IPD is becoming one of the hottest research topics.Analyzing the China’s pension system we figure out those new employees who join pension system after1997may influence the scale of IPD. Considering new employees will make current IPD measurement model more useful and practical. We build dual random model under both closed-system and open-system and estimate prospect IPD scale base on the policy and predicted data.We use Monte Carlo simulation to get empirical distribution of IPD. On the basis of Glivenko-Cantelli theorem we can use empirical distribution of simulated samples to replace the real distribution. In this model rate and age-at-death are random variables. We choose standard Ornstein-Uhlenbeck process to model the instantaneous rate and use grey prediction model to prediction the scale of "new employees". We get empirical distribution of IPD under both closed-system and open-system which help us get the conclusion that "new employees" will expand the scale of IPD.Even though there are some shortcomings about this econometric model. We propose a new way to estimate the prospective scale of IPD and propose several ways to resolve IPD problem.