scholarly journals The New Fertility Policy and the Actuarial Balance of China Urban Employee Basic Endowment Insurance Fund Based on Stochastic Mortality Model

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yuantao Xie ◽  
Xinzhu Zhang ◽  
Huijuan Lv ◽  
Xiaojing Guo
Keyword(s):  
Growth Rate ◽  
Social Factors ◽  
Insurance Fund ◽  
Endowment Insurance ◽  
Stochastic Mortality ◽  
Mortality Model ◽  
Fertility Policy ◽  
Basic Endowment Insurance ◽  
Stochastic Mortality Model ◽  
The Impact

This study aims to investigate the impact of China’s new fertility policy on the actuarial balance of its Urban Employee Basic Endowment Insurance (UEBEI) fund, with stochastic mortality model included to address the longevity risk. Combined with the latest UEBEI policy, this paper constructs an actuarial balance model and introduces the growth rate of wage, the age of employment and the age of retirement, the rate of payment, the rate of replacement, the annual rate of pension adjustment, and the population in terms of age into the model, which arise from the rate of payment, average wage, and personal and social factors. This study uses the sixth population census data by age group and gender to employ empirical analysis. The sensitivity analysis of China’s basic pension insurance fund balance is made. It is concluded that the increase in the growth rate of wage caused by social factors, the increase of fund investment returns, the delay of retirement, and the increase in the fund collection rate are all conducive to the sustainability of the UEBEI fund.

Pricing longevity-linked derivatives using a stochastic mortality model

2019 ◽  
Vol 48 (24) ◽  
pp. 5923-5942
Author(s):  
Yige Wang ◽  
Nan Zhang ◽  
Zhuo Jin ◽  
Tin Long Ho
Keyword(s):  
Stochastic Mortality ◽  
Mortality Model ◽  
Stochastic Mortality Model

scholarly journals A Square-Root Factor-Based Multi-Population Extension of the Mortality Laws

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2402
Author(s):  
Petar Jevtić ◽  
Luca Regis
Keyword(s):  
Maximum Likelihood ◽  
Model Parameters ◽  
Time Varying ◽  
Square Root ◽  
Stochastic Mortality ◽  
Mortality Model ◽  
Model Based ◽  
Males And Females ◽  
Quasi Maximum Likelihood ◽  
Stochastic Mortality Model

In this paper, we present and calibrate a multi-population stochastic mortality model based on latent square-root affine factors of the Cox-Ingersoll and Ross type. The model considers a generalization of the traditional actuarial mortality laws to a stochastic, multi-population and time-varying setting. We calibrate the model to fit the mortality dynamics of UK males and females over the last 50 years. We estimate the optimal states and model parameters using quasi-maximum likelihood techniques.

scholarly journals Comparison of Stochastic Mortality Model for Wider Age Range

MATEMATIKA ◽  
2018 ◽  
Vol 34 (2) ◽  
pp. 227-233
Author(s):  
Siti Rohani Mohd Nor ◽  
Fadhilah Yusof ◽  
Arifah Bahar
Keyword(s):  
Risk Exposure ◽  
Longevity Risk ◽  
Model Structure ◽  
Research Directions ◽  
Linear Pattern ◽  
Stochastic Mortality ◽  
Mortality Model ◽  
New Research ◽  
Age Range ◽  
Stochastic Mortality Model

The incorporation of non-linear pattern of early ages has opened new research directions on improving the existing stochastic mortality model structure. Several authors have outlined the importance of encompassing the full age range in dealing with longevity risk exposure by not to ignore the dependence between young and old age. In this study, we consider the two extensions of Cairns, Blake and Dowd model that incorporate the irregularity profile seen at the mortality of lower ages which are Plat and O’Hare and Li. The models’ performances in terms of in-sample fitting and out-sample forecasts were examined and compared. The results indicated that O’Hare and Li model performs better as compared to Plat model

An Empirical Study on Residents' Consumption Changes Based on the Development of Commercial Annuity

2020 ◽  
Vol 8 (8) ◽  
pp. 110-122
Author(s):  
Jiaxuan Zhou
Keyword(s):  
Household Consumption ◽  
Income Level ◽  
Endowment Insurance ◽  
Pension Insurance ◽  
Insurance System ◽  
Dynamic Panel Regression ◽  
Basic Endowment Insurance ◽  
Optimization And Upgrading ◽  
The Impact ◽  
Pension Insurance System

The relationship between the level of pension insurance development and the consumption of Chinese residents is a topic of constant debate. However, few scholars have analyzed residents' consumption behavior based on the level of commercial annuity development.  Using China's 2010-2018 inter-provincial panel data, this article builds a dynamic panel regression model to explore the impact of the development of commercial annuities on household consumption and its structure. In addition, the paper also compares the impact of the protection levels of basic pension insurance and commercial annuity on household consumption. The results show that the per capita disposable income of residents is still the main factor that promotes residents’ consumption. The improvement of commercial annuity and basic endowment insurance will help to promote residents' consumption, and the effect of commercial annuity's promotion on residents' consumption is more significant. In promoting the optimization and upgrading of consumption structure, commercial annuity insurance plays a more significant role than residents' income level and basic pension insurance. Based on the regression results, this article suggests that efforts should be made to increase the income level of residents and promote consumption from the root cause. At the same time, it is necessary to improve the commercial pension insurance system as soon as possible and steadily promote the coordinated development of the "three pillars" pension insurance system.

scholarly journals A Bayesian approach to developing a stochastic mortality model for China

2019 ◽  
Vol 182 (4) ◽  
pp. 1523-1560
Author(s):  
Johnny Siu‐Hang Li ◽  
Kenneth Q. Zhou ◽  
Xiaobai Zhu ◽  
Wai‐Sum Chan ◽  
Felix Wai‐Hon Chan
Keyword(s):  
Bayesian Approach ◽  
Stochastic Mortality ◽  
Mortality Model ◽  
Stochastic Mortality Model
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