人口研究 ›› 2010, Vol. 34 ›› Issue (1): 95-105.

• 论文 • 上一篇    下一篇

城镇不同社会医疗保险待遇人群死亡率交叉现象研究

黄枫1吴纯杰2   

  1. 1 西南财经大学经济与管理研究院;2 上海财经大学统计与管理学院
  • 出版日期:2010-01-29 发布日期:2012-11-25
  • 通讯作者: fhuang@mail.swufe.edu.cn
  • 作者简介:1 西南财经大学经济与管理研究院博士研究生;2 上海财经大学统计与管理学院副教授
  • 基金资助:

    上海财经大学211工程3期;上海市重点学科建设项目(编号:B803)资助

Old Age Mortality Crossover in China:Does the Public Health Insurance Matter

Huang Feng1, Wu Chunjie2   

  1. 1 Research Institute of Economics and Management , Southwestern University of Finance and Economics ; 2 School of Statistics and Management , Shanghai University of Finance and Economics.
  • Online:2010-01-29 Published:2012-11-25
  • Contact: fhuang@mail.swufe.edu.cn
  • About author:1 PhD student, Research Institute of Economics and Management , Southwestern University of Finance and Economics; 2 Associate Professor, School of Statistics and Management , Shanghai University of Finance and Economics

摘要: 本文使用"中国老人健康长寿影响因素研究"(Chinese Longitudinal Healthy Lon-gevity Survey,CLHLS),2002~2005年调查数据对我国不同社会医疗保险待遇的老年人口的死亡率交叉现象进行了研究。运用离散时间的死亡风险分析,文章的发现支持"选择性死亡"的理论,即无社会医疗保险的人群,60岁时死亡率一直高于享受医保人群,使得无医保人群中强健的个体幸存下来;随着年龄的增长,这种选择机制的作用逐渐表现为"死亡率逆转",即无医保人群的平均死亡率在大约96岁以后开始低于享受医保人群。研究显示,我国享受社会医疗保险的老年的生存优势一直存在至96岁高龄,医疗保险对于老年人口的健康有着显著而长远的积极影响。

关键词: 社会医疗保险, 死亡率交叉, Logistic回归

Abstract: This study analyzed data of respondents who were age 60 or over in Wave 2002 of Chinese Longitudinal Healthy Longevity Survey and whose survival statuses were followed in Wave 2005. Using discrete-time hazard techniques to model the risk of dying over the span of almost three years,the empirical results indicates that selective mortality exists between the elder with and without public health insurance (PHI):those subgroups without PHI systematically experience higher mortality at younger age,leaving a more robust group of individuals in the surviving population.As age advances,this group exhibits lower mortality compared with those with PHI.There is a mortality crossover at age 96 among Chinese elders,indicating that PHI has a lasting and positive effect on health and longevity.

Keywords: Public Health Insurance (PHI), Mortality Crossover, Logistic Regression