The disability risk among elderly people is an important problem in the context of population aging.Existing research often ignores the censoring properties of disability data and cannot make full use of micro-data information.This paper presents a new method for modeling the disability risk among old people.First,considering the interval censoring and right-censoring of disability data in the Chinese Longitudinal Healthy Longevity Survey(CLHLS),this paper classifies the data according to the transition time from the healthy state to the first disability state.This paper also uses the CLHLS death survey to add information on disability prior to an individual's death.This paper uses the semi-parametric transformation model in survival analysis to construct a model of disability time,which estimates and predicts the elderly disability rate more accurately.Compared with the traditional model,the new model can incorporate variables such as age,gender,and education level into the model,making a more detailed and accurate analysis of the disability risk for people with different characteristics.Our model provides an empirical basis for improving China's long-term care insurance system.
关键词
长期护理保险/失能风险/删失数据/半参数转换模型
Key words
Long-term Care Insurance/Disability Risk/Censored Data/Semi-parametric Transformation Model
维普
万方数据