We employed the Generational Accounting model in estimating the generation-specific lifetime (both past and the future) benefits/burdens and income and evaluating their values as of 2010, thus estimating the lifetime net burden ratio (= lifetime net burden/lifetime income). As a result, the...

This study examines whether or not aging is increasing the political influence wielded by Japan’s elderly and promoting a so-called “gray democracy.” Using a median voter model based on data from Japan’s 47 prefectures during the period from 2000 to 2010, we examined the relationship...

We build a computable OLG model with monetary growth to calculate the optimal level of inflation rate for Japan, and to study policy reforms make any quantitative impacts on it. Four main results were obtained: (i) the optimal inflation rate for Japan is calculated around 1.0%; (ii) the...

To quantify the impacts of immigration and fiscal reconstruction on the Japanese economy, we present a dynamic computable general equilibrium OLG model with an overlapping generations structure. We use a total of 16 countries and regions, both including those that are industrialized, such as...

Our study employs an OLG model under which political strengths of different generations (the working and retirees with and without children) determine the distribution of the fiscal burden between the generations, including the future generation. We investigate the relationship between the...

We have developed a computable endogenous growth OLG model generated by the accumulation of human capital. To study whether policy reform against aging make any quantitative impacts through human capital formation on the Japanese economy and whether it has long-run effect, we simulate two policy...

We constructed an overlapping-generations model with endogenous fertility to analyze the effects of child benefits and pensions on the welfare of current and future generations. The following results were obtained. First, in the case without pension and accelerated fiscal reforms, the best...