An empirical analysis of US and Japanese health insurance using age–period–cohort decomposition
使用贝叶斯队列模型分解美国和日本家庭健康保险支出的年龄、时期和队列效应，发现年龄效应影响最大而队列效应可忽略，对社会保障政策有启示。
Aggregate data on household health insurance expenditure in the US and Japan that are classified by period and age are decomposed into age, period, and cohort effects by using the Bayesian cohort models. These models are developed to overcome the identification problem involved in cohort analysis. Despite the differences between the health insurance systems of the two countries, three interesting empirical findings are obtained. First, in both the countries, the age effects are the most influential, and the cohort effects have negligible influence. The latter provides a striking policy implication since the generational imbalance in social security expenditures is widely recognized in developed countries. Second, in both the countries, the period effects show a roughly upward trend. Finally, the age effects exhibit a roughly upward movement for all age groups in the US; however, in Japan, these effects show a downward movement for the 55-59 age group due to the changes in the health insurance system on retirement.