Financial Problems and Future Prospect

The Japanese government's standard forecast on the future senior ratio is based on the assumption that the total fertility ratio will recover from the present rate of, 1.43 to 1.63 in the near future and that the average life expectancy at birth will extend upward modestly as Chart 9 shows. If the fertility rate does not recover and life expectancy becomes longer, the proportion of the elderly to the total population in 2030 will be higher than 28%. The elderly population will increase, while the population of the productive age group, 15 to 65 years old, which had been increasing, began to decline from 1996 (See Chart 23). As a result of this historical change, the proportion of the aged to the productive age population and to the working population will increase markedly after the middle of the 1990s.

Main Factors that Decide Social Security Costs

It is a well-known fact that social security costs as a ratio of national income depend significantly on the proportion of the elderly to the total population and productive age population (Wilenski, 1975). The time series analysis from 1960 to 1994 and cross-section analysis based on the 47 prefectures in Japan confirms this assumption.

Chart 24 shows the relationships among the social security costs/national income ratio and related indicators.

The chart and factor analysis on these indicators suggest that there are four main factors that may explain the time series fluctuation of the social security/national income ratio. They are aging factor, growth factor, employment factor and political factor. The figures in Chart 24 show the correlation coefficient. Table 6 also suggests that ageing factor, income growth factor, employment factor and political factor are important factors that decide the behaviour of the social security benefits/national income ratio.

Econometric Foundation

The percentage ratios of social security benefits, pension benefits and health and medical service benefits vis-à-vis national income have increased as aging of the population proceeds as Chart 25 shows.

Other important variables to explain the behavior of social security benefits are economic fluctuations and the employment situation. In the case of health and medical services, the percentage ratio of out-of-pocket payments influences expenditure on health and the medical services.

Multiple regressions (OLS) based on annual data between 1960 and 1994 in Table 6 suggest that the proportion of elderly people to the total employed labour force {N_o / N_e in regression (1}, (2) and (3)} is the most important explanatory variable of the change in social security benefits, pension benefits and health insurance benefits as percentage of national income.

Regressions (1)~(3) confirm again that the senior ratio, income increase, the rate of unemployment that represents economic fluctuations and the political factor are the main variables that explain the behaviour of the social security benefits/national income ratio. The above analysis also suggests that maintaining steady economic growth and full employment are effective in moderating the increase of social security costs in national income. This analysis seems to support the argument that productive welfare policy is helpful for sustainable welfare policy.

Correlation observed by time-series analysis is sometimes misleading, but the cross-section analysis based on the 47 prefectures in Japan supports a part of the above findings. The analysis shows that the per head costs for personal social services and medical costs have positive correlation with the senior ratio as Chart 26 shows. Chart 26 A illustrates the relationship between the elderly ratio of each prefecture with per head personal social services costs. Tokyo and Kobe are exceptionally far from the regression line. The special expenditure for an earthquake for those who lost housing may explain why Kobe is exceptional. The personal social services in Tokyo have been exceptionally high since the period of a socialist governor. Per head medical costs are also positively correlated with the senior ratio as Chart 26 B shows.

Chart 26 C shows the relationship between the proportion of the elderly (65 years old and over) to the total population and the number of facilities for the elderly. This chart suggests a positive correlation exists between them. The number of welfare facilities for the elderly per 100,000 population in Shimane Prefecture, where the proportion of the elderly is the highest, is about four times larger than that of Kanagawa Prefecture where the proportion is still very low. This chart suggests how many welfare facilities and sheltered housing will be required in Japan when the proportion of the elderly becomes more than 20%.

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