Abstract
By using a microsimulation model named INAHSIM, we conducted a household projection in Japan for the period of 2011–2060. Due to rapid aging of the population, the distribution of the elderly (65 years old or older) by living arrangement and dependency level has a profound impact on the future social burden. In this paper, we measured the social burden of the elderly by three variables: (1) institutionalization rate (percentage of the elderly living in institutions), (2) parent-child ratio (relative number of old parents taking into account the number of brothers and sisters), and (3) one-year transition matrix of the elderly by household type. Especially, the choice of the elderly among (a) living independently, (b) coresident with child households, and (c) moving to institutions are crucial indicators for the future social burden of the elderly in Japan.
Highlights
The household is one of the most important statistical bases for policy formulation on health and welfare
According to the 2011 simulations, the total population continues to decline throughout the projection periods, while aging of the population will continue until 2050 (Figure 1)
In 2010, among the elderly population, 16.9 percent live in one-person households, 37.2 percent in couple-only households, and 42.3 percent live with the child generation
Summary
The household is one of the most important statistical bases for policy formulation on health and welfare. The household is still an important unit for various policies, and elderly in one-person household tend to require support of various kinds in aging society. Statistical information on households and families is still inadequate, to understand the dynamic process of formation and dissolution of households and families in a systematic and coordinated way. Dynamic microsimulation models are considered to be the most suitable method to observe the dynamic evolution of households and families and to forecast their future trends. The dynamic microsimulation method does have some drawback, including difficulties in obtaining the initial population as well as estimating the transition probabilities. INAHSIM-II is a solution to avoid the difficulty to obtain initial population for the model
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