Financing Health Care in Japan: A Fast Aging
Population and the Dilemma of Reforms∗
Minchung Hsu†
National Graduate Institute for Policy Studies (GRIPS), Tokyo
Tomoaki Yamada‡
School of Commerce, Meiji University, Tokyo
This version: December 2011

Abstract
This paper is aimed at providing a quantitative analysis of the impact of
population aging in Japan on financing its universal health insurance systemand potential reform policies. We construct a general equilibrium life cycle
economy that is used to study the impact of an aging population on household’s work and savings behavior, as well as on aggregate output and welfare.
In particular, taking 2010 as an initial steady state, we calculate the transition
path predicted by our model as the population structure changes and medical
costs increase. We also evaluate various policy alternatives designed to lessen
the negative impact of aging on the economy. We show that even though the potential reforms improve the welfare of the future generation significantly, there
is a political difficulty to implement any of the reforms.
Keywords: Universal Health Insurance, Population Aging, JapanJEL Classification: E21, H51, I10∗ We thank Julen Esteban-Pretel, Gary Hansen, Selo İmrohoroğlu, Yasushi Iwamoto, Mari

Kan, Nao Sudo, C.C. Yang, conference participants at the 2011 Annual Meeting of the Society for
Economic Dynamics and the 26th Annual Congress of the European Economic Association, andseminar participants at the GRIPS, Osaka University, Institute of Economics Academia Sinica,
Meiji University, Policy Research Institute, Macau University and the Bank of Japan for many
useful comments and discussions.
† E-mail: minchunghsu@grips.ac.jp‡ E-mail: tyamada@meiji.ac.jp

1

1 Introduction
This paper aims to provide a quantitative analysis of the impact of population aging on the cost of maintaining a universal health care system. We focus
on Japan because it has a public universal health insurance (UHI) system thatprovides health insurance coverage to all its residents, as in most OECD countries, and its population has been aging dramatically over the past two decades.
We study the tax burden associated with financing the UHI and the impact it
has on the economy as the population ages. Potential reforms of the UHI and
how it is financed will also be evaluated.
The current cost of health care in Japan is relatively low (about 6.6% of GDP
or 9.1% of National Income in 2005) compared with other OECD countries. In
addition, the Japanese have among the highest life expectancy and lowest infantmortality in the world. The health care system in Japan seems to be in remarkably good shape. However, as the population ages, this low-cost is probably
not sustainable with the current framework and financing methods. Japan already has the world’s oldest population, and it is projected that 40% will be 65
or older in 2050 (see Figure 1).
The population aging affects the health care system through two channels.
First, as the fraction of the population over 65 increases, the fraction that pays
taxes and premiums that finance the system decreases. In particular, one quarterof the program’s costs are financed by general government revenues, and therest is paid by premium (a payroll tax) levied on employers and workers, andco-payments made those seeking medical care. It is obvious that the burdenof financing health care is mainly on the working-age population (age 15-64),
which is projected to shrink to 51% of total population in 2050 with an old-age
dependency ratio above 75% (see Figures 1 and 2).1
Second, the elderly face higher health risks and need much more care than
young people. The data show that the average per-person medical cost for those
aged 65 and above is 241.8% as of the average of the total population, and it isabout 4 times that of those under age 65. Table 1 presents medical costs per
capita for different age groups. A larger elderly population implies higher per
capita medical costs. Figure 3 shows the trend of medical costs in Japan. Dueto population aging, if the current system is to be maintained, either the government subsidy or the insurance premium, which is a tax on labor income,charged to workers and employers has to increase to finance the extra cost of
1 Data source: National Institute of Population and Social Security Research, Japan.

2the health care system. Either way, the financial burden on the working age
population will increase.
In this paper, we construct an equilibrium life cycle model and carry out
quantitative exercises to help understand: 1) the impact of demographic change(in particular population aging) on the costs of financing the UHI; 2) the impactof the above changes on household working and saving behavior, as well as on
aggregate economic performance; and 3) the effects of potential reforms of the
UHI and the methods used to finance the program; 4) how likely are the reforms
to happen? Our goal is to identify and compare potential government policy
responses to the ongoing changes in the age structure of Japan’s populationand the impact this will have on the country’s health care system. The politicaldifficulty of the reforms will be also discussed by an investigation of welfarechanges in current and future generations. Transition paths corresponding toeach of potential reforms are considered to provide a precise analysis of thewelfare changes for the current generation that affects the political acceptanceof the reforms.
We find that the fast population aging increase the aggregate medical carecost, and therefore would increase the burden of financing the UHI – it willneed additional 8.8% of labor income in 2050. If the medical price grows fasterthan productivity by 0.6% per year, as observed in the US, labor tax (including the UHI premium tax) has to increase 13.6 percentage points to finance the
UHI in 2050. The high labor tax rate further discourages labor supply when
the working-age population is shrinking due to population aging. Potential
reforms to reduce the labor tax burden, which are discussed in this paper, include an increase in UHI co-payment and raising consumption tax. We present
the welfare gains of the reforms relative to the benchmark where only the labor income tax (including payroll and UHI premium taxes) adjusts to balance
the government budget constraint. In this study, we perform both steady statecomparison and transition analysis to understand the welfare implications forthe future and the current generations, respectively.
The method of our transition analysis is based on Nishiyama and Smetters(2005, 2007), which explicitly consider transition path of fiscal reforms and social security reforms. We find that even though the reforms reduce the tax burden on the working-age population and significantly improve the welfare of the
future generation, the current generation will suffer except young persons. In
addition, older people would encounter higher welfare loss since they have lessor even no time to prepare for the policy changes when they are working. This3

finding indicates that the reforms are difficult to be supported by the majorityof the population.
Previous studies have considered health/medical expenditure shocks in life
cycle models. Hubbard, Skinner, and Zeldes (1995) consider medical expenditure shocks, which might cost more than an individual’s wealth, and investigate
the role of means-tested social insurance system on the savings. French (2005)
estimates a life cycle model and studies the effect of uncertain health status on
retirement behavior. De Nardi, French and Jones (2010) find that uncertain expensive medical expenditure and the risk of long-living are the main reasons
for retirement saving behavior, and the bequest motive has small impact on theold saving. French and Jones (2010) also estimate a life cycle model to study
the effects of health insurances on retirement behavior. In the previous studies,
the general equilibrium effects are not considered. This study investigates theimpacts of population aging and potential reforms, which are likely to change
aggregate labor supply and capital stock and lead to price changes. To provide
a more precise analysis, we undertake a general equilibrium life cycle model tocapture the interaction between individual behavior and aggregate economy.
In the literature, a general equilibrium life cycle framework has been used to
study various social programs. One can see Attanasio et al. (2007), Hugget andParra (2009), and İmrohoroğlu and Kitao (2010), for example. However, withouta few exceptions by Jeske and Kitao (2009) and Attanasio et al. (2010), health insurance systems are out of their scope. Attanasio et al. (2010) is a study close tous, which investigates the impact of population aging on financing Medicare, apubic health insurance program covering individuals aged 65 and above in theUS, and potential reforms. Because of the immigrants, population aging in the
US is not as fast as in Europe and not comparable with it in Japan. We study
Japan that is a good example to understand the impacts of a fast aging population. Moreover, besides evaluating the welfare changes of potential reforms
for the further generation (i.e. in the steady state), as in Attanasio et al. (2010),
we further discuss the welfare implications of potential reforms to the current
generation, whose support is politically crucial to a reform policy, by analyzing
the corresponding welfare changes along the transition.
This paper proceeds as follows. In Section 2, we briefly describe the healthinsurance system in Japan. In Section 3, we construct a general equilibrium lifecycle model. In Section 4, we calibrate parameters to match Japanese economy.
In Section 5, we discuss quantitative results. We conclude in Section 6.

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2 Health Insurance System in Japan
As in many OECD countries, Japan provides an public universal healthinsurance system, which covers all of the citizens including employee, selfemployed, unemployed, children and retirees. There were already some independent health insurance programs based on jobs and occupations before
World War II.2 The Japanese government re-organized those health insurance
programs, and achieved the universal health insurance coverage in 1961.
The actual application of the insurance to any given person is complicatedand depends on several factors: age, job/occupation and employment status
and so on. There are hundreds of insurers, which are managed by societies orcentral/local governments, providing health insurance coverage and collecting
premiums. Although there exist many different insurers, they are not to choose.
The insurer assigned to a specific individual is determined according to theabove individual factors. However, all the insurance benefits are set by thegovernment regardless the insurer.
The current public health insurance can be divided into three categories:(a) employment-based health insurance (Shakai Kenkou Hoken), (b) communitybased health insurance (Kokumin Kenkou Hoken) and (c) health insurance for theelderly (Rojin Kenkou Hoken).
Most workers are included in the employment-based health insurance system. There are several health insurance schemes based on occupation:• Kenko Hoken: Most employees who work in private sector are covered by
Kenko Hoken. Depending on the size of firms they work, there are two
types: society-managed health insurance and government-administeredhealth insurance. Employee of large firms are covered by the societymanaged health insurance, and those of small firms are covered by the thegovernment-administered health insurance. There were about 1.5 thousand societies under the society-managed employment-based health insurance scheme in 2009.
• Kyosai Kumiai: Employees of public sectors (both central and local public sectors) and teachers are covered by Kyosai Kumiai, which is also an
society-managed health insurance. There were 76 societies under thisscheme in 2009.
2 For a brief history and effects of the development of universal public health insurance sys-

tem in Japan, see Kondo and Shigeoka (2011).

5

The community-based insurance, Kokumin Kenkou Hoken, covers people whoare not included in the category (a), e.g., the self-employed, the unemployed,
irregular employees and retired people.3 It is organized by local governments.
There were about 2 thousand insurers.
Membership of one or the other system is compulsory and not to choose.
Monthly premiums are calculated slightly differently for each insurer/socieity
but are based mostly on salary (equivalently a labor income tax). The soceities/insurers
also receive government subsidies for the insurance payment. The general coverage of the UHI is 70% of medical expenditures (i.e. a 30% co-payment). For
senior people aged between 70 to 74, the co-payment rate is reduced 20% exceptthat their income is higher than a threshold.
Health insurance for the elderly was introduced in 1983 to spread the burdenof providing health care for this group equally among various health insurance
insurers. The health insurance for the elderly provides coverage for persons
aged 75 and above. The co-insurance rate (or co-payment rate) of the healthinsurance is 10% except that the income is above a threshold and it becomes
30%. This insurance is highly subsidized. About 50% of the cost of this healthinsurance for the elderly is from public subsidy. The subsidy is shared by state,
prefectures, and municipalities with a 4:1:1 cost-sharing rule. About 40% of theinsurance cost is financed by young people’s premiums collected by all the insurers/societies. Only 10% is contributed by the elderly’s premium payments.
In total, the government subsidy to the UHI system contributes about 25% of
the total medical care cost. The rest is financed by premiums (mainly on young
people) and co-payments.

3 ModelA general equilibrium life-cycle model with national health insurance, endogenous labor supply and incomplete markets is constructed in order to carryout our analysis. We focus on the steady state and transition dynamics.

3.1 Demographics
The economy is populated by overlapping generations of individuals of age
j = 1, 2, ..., J. The lifespan is uncertain. An individual of age j survives until next
3 Dependent children and spouses are covered by household heads’ health insurance.

6period with probability ρ j which depends on her/his age j. When individuals
reach age J, then ρ J = 0 and will leave the economy next period. The size of newcohort grows at a rate g. The population of age j is denoted by μ j , which evolvesρ

μ j+1 = 1+j g μ j , and the total population is normalized to one, ∑ jJ=1 μ j = 1.

3.2 Endowment, Income Uncertainty and Preferences
Individuals enter the economy with no assets and are endowed with one
unit of time. They can spend the time on market work for earnings or on leisure.
If they decide to spend n hours on the market work, their earnings are given aswη j zn, where w is the market wage, η j is the age-specific productivity, and z is
idiosyncratic labor productivity that evolves stochastically to characterize theincome uncertainty. η j is zero after retirement age jss .
Individuals value consumption and leisure over the life-cycle and determine
the sequence of consumption and labor supply according to a utility functionu( c, n), which is compatible with balance growth path:u ( c, n) =c σ ( 1 − n ) 1− σ
1−γ

 1− γ;where γ governs the intertemporal elasticity of substitution.

3.3 Health, Medical Expenditure and National Health Care
3.3.1 Heath Status and Medical Expenditure Uncertainty
Agents face exogenous uncertainty about their health status h. The healthstatus evolves according to the Markov chain among three states of good, fair,and bad, {h g , h f , hb }, with a transition matrix π j (h , h) that depends on age. Individuals face an idiosyncratic medical expenditure shock x j (h) in each period.
3.3.2 Universal Health Insurance
Agents can partially insure medical expenditure risks with access to healthinsurance that covers a fraction ω j of realized medical expenditure x. The public
UHI is available to every resident, and financed by an income-related premium(a payroll tax) and government general revenue. The coverage rate of medical
expenditures depends on age j. As will be discussed later, the co-payment rate,7

1 − ω j , is 30% under age 70 (i.e. a 70% coverage rate), 20% between 70-74, and
10% over age 75.
To consider the effect of future increases in medical costs, we also estimate
the growth of medical expenditures q, which implies that individuals pay (1 −ω j )qx. In the benchmark case, q is set equal to one.

3.4 Public Pension
The public pension program provides the elderly with a benefit ss when theyreach the eligibility age of jss and retire. The program is financed by the social
security tax τ ss imposed on labor income of the working population.

3.5 Production Technology
On the production side, we assume that there is a continuum of competitive
firms operating a technology with constant returns to scale. Aggregate output
Y is given by
Y = F (K, L) = AK θ L1−θ ,where K and L are the aggregate capital and effective labor employed by thefirm’s sector and A is total factor productivity which we assume to be constant.
Capital depreciates at rate of δ every period and θ denotes the capital income
share.

3.6 Financial Market Structure
Individuals can hold assets that are non-state contingent claims to capital.
The rate of return earned from these assets is denoted by r. Households canpartially insure themselves against any combination of idiosyncratic labor productivity shocks and medical expenditure shocks by accumulating precautionary asset holdings. While they are allowed to insure themselves by accumulating positive asset holdings, they cannot carry debt, a ≥ 0. This borrowing limit specially affects the asset holding decision of low-wealth households
since they cannot smooth their consumption over time when their disposable
incomes falls.

8

3.7 Government
In addition to the UHI and social security, the government also provides
means-tested social insurance (public assistance) in this economy. The government guarantees a minimum level of consumption c by supplementing theincome in case the household’s disposable income plus assets (net after medical expenditure) falls below c. We consider a simple transfer rule proposed by
Hubbard et al. (1995). The transfer T will be made if the household’s disposable
income plus assets (net after medical expenditure) is smaller than a minimum
level of consumption. The transfer amount will be exactly equal to the difference.
Government’s revenue consists of revenues from different tax instruments,
labor income tax τ l , capital income tax τ k , consumption tax τ c , social security
tax (pension payment) τ ss , and the UPHI premium pmed . The government uses
its revenue to finance all public programs and its own consumption G.

3.8 Household’s Problem
The states for an agent is summarized by a vector s = ( j, h, a, z), where j
is age, h is health status, a is asset holdings brought into the period, and z is
the idiosyncratic shock to labor productivity. The household’s problem can be
expressed as:  
V (s) = max u ( c, n) + ρ j βE V s,
c,n,a

subject to(1 + τ c )c + a = W + T,W ≡ y(n, j, z) + (1 + (1 − τ k ) r ) (a + b) − 1 − ω j qx,y(n, j, z) = (1 − τ l − τ ss − pmed )wη j zn + ss( j)T = max{0, (1 + τ c )c − W }ss j =

ss if j ≥ jss ,0 otherwise.

where T is the transfer made by the means-tested social insurance system, which
ensures that agents will not fall into an undesired situation with negative wealthand consumption; ss is the social security benefit, and b is the lump sum transfer of accidental bequests. For simplicity, the public pension benefit is constant9

for all individuals. We assume that the public pension benefit is a constantfraction of efficient labor, φwL, where the replacement rate φ is endogenously
determined from a budget constraint for soical security system.
Accidental bequests are redistributed by a lump-sum transfer:b =(1 − ρ j )a  dΦ(s ).

3.9 Government Budget Constraints
The government finances a fraction ψ of the UHI cost with general revenue.
Individuals pay for the remaining fraction, 1 − ψ, through the mandatory UHI
premium payment. Currently ψ is equal to 0.25 in Japan. The government budget constraint is as follows:[τ l wη j zn + τ k r (a + b) + τ c c]dΦ (s) = ψTax Revenue(ω j qx )dΦ (s) +TdΦ (s) + G

UHI subsidy( pmed wη j zn )dΦ (s) = (1 − ψ )(ω j qx )dΦ (s)Premium

where Φ( s) is a distribution function over state variables. In the benchmark,we set the tax rates (τ k , and τ c ) equal to the current rates (in 2010) and set G
equal to its current value as a percentage of GDP. In experiments with predicted
population aging or medical care cost increases, we suppose the government
will adjust the payroll tax to balance its budget and keep the values for G, τ k ,and τ c fixed. This allows us to investigate how large is the extra burden on
individuals (measured by changes in τ l and pmed ) caused by the cost changes
for the UHI.
The social security public pension system is self-financed with a Pay-AsYou-Go scheme:(τ ss wη j zn) dΦ( s) = (ss) dΦ(s ).
From the assumption that the public pension benefit is a constant fraction of thejrefficient labor L, the replacement rate φ is determined to satisfy ∑ j=1 μ j τ ss =J∑ j= jr+1 μ j φ.

3.10 Stationary Recursive Competitive Equilibrium
A stationary recursive competitive equilibrium is defined as a set of household decision rules for asset holding a  , labor supply n and consumption c; a10set of firm decision rules for capital rented K and effective labor employed L; aprice system w and r; a government policy of tax rates τ ss , τ l , τ k and τ c , public
pension benefits ss, an UHI premium pmed and a subsidy ratio ψ; and a distribution of households over the state variables Φ(s ), such that:a) given the price system, the decision rules of K and L solve the firm’s problem;b) given the price system and the goverment policy, the decision rules (a  , n, c)
solve the household’s problem;c) government policies (τ ss , τ k , τ l , τ c , ss, pmed , ψ) satisfy the government’s budget constraints;d) Φ(s ) is stationary;e) all markets clear: L =b);(η j zn) dΦ( s) and K  =a dΦ( s) (or K =adΦ (s) +f) resource feasibility condition is satisfied
Y = C + K  − (1 − δ)K + qX + G;
where C is the aggregate consumption, and X is the aggregate medical
expenditure.

4 Calibration
In this section, we describe calibration and parameter selection. Table 4 summarizes some key parameters.

4.1 Preference
We set the subjective discount factor β equal to 0.98 so that the after-tax interest rate and the capital-output ratio K/Y in the model matches recent values
for Japan. The elasticity of intertemporal substitution 1/γ is assumed to be 0.5,
i.e., γ is set at 2, and the share of labor supply parameter σ is set at 0.33.

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4.2 Production Function
Parameters of the production function, capital’s share θ and the depreciation rate δ, are taken from İmrohoroğlu and Sudo (2010). They estimate theseparameters from the SNA by extending Hayashi and Prescott (2002)’s calibration to the current Japanese economy. We set the capital share to be 0.377, andthe depreciation rate 0.08 respectively.

4.3 Demographics and Survival Probability
A household enters the economy at age 20, retires at 65, and lives at most until 100. The National Institute of Population and Social Security Research (IPSR)
provides future projections on Japanese demographic changes. The most recent projection was estimated in 2006, and provides forcasts of demographic
changes from 2005 to 2055. The projection consists of three variations on fertility rates, high, medium, and low, and also three variations on mortality rates.
Thus, we have nine projections. We use medium variants on both fertility andmortality rates. For stationary state comparison, the survival probabilities {ρ j }are taken from the life table for males in 2010 (initial stationary state) and 2050
(final stationary state). The population growth rate g is set at 0 in the initial stationary sate, and it is set at −1.5% at final stationary state. Figure 4 and 5 plots
the actual and simulated population distribution in 2010 and 2050 respectively.
The faction of retired households, which is defined as the ratio of households
aged over 65 to those between 20 and 64, in the model (26.43%) is quite close
to the actual data (26.75%) in 2010. We assume the negative population growthrate because the actual population distibution is extremelyl aging in 2050. Under the assumption of negative population growth rate, the fraction of retired
households in the model (45.0%) is close to the data (44.12%).

4.4 Medical expenditure
Micro-level panel data of medical expenditure are not publicly accessible inJapan. There is no database like the Medical Expenditure Panel Survey (MEPS)
in the US, which is widely used to calibrate medical expenditure states and transition probabilities.4 To do a careful calibration for Japan, our main source is thereport of Kan and Suzuki (2005). Kan and Suzuki studied the concentration and
4 See, for example, Jeske and Kitao (2009) and Attanasio et al. (2010).

12

the persistence of health care expenditures in Japan. They had a special permit
to access the health insurance claim data from 111 Japanese health insurance
societies between 1996 and 1998. The data are panel and contain 35,970 individuals with age between 0 to 70.
4.4.1 Transition Probabilities
Kan and Suzuki (2005) analyzed the transition of medical expenditure in 5
age groups (0-17, 18-35, 35-45, 46-55, and above 55). Within each age group,
they divided the samples into 10 medical expenditure quantiles and reported
the corresponding transitions from 1996 to 1998.
Our purpose is to estimate the annual transition for medical expenditures
for each age (from 20 to 100). To have a clear transition patterns over age, we
re-classify the 10 quantiles to 3 states of medical expenditures: ‘low’, ‘middle’and ‘high’. The category ‘low’ includes those in the bottom 50% of medical
expenditures, the ‘middle’ contains the 6th quantile to the 9th quantile, and the‘high’ category represents the top 10% expenders. The three states are unevenly
classified such that they are able to capture the long-tail in the distribution of
the medical expenditures and a small probability of incurring very large andcatastrophic expenditures.
The original report in Kan and Suzuki (2005) present the transition of medical expenditure in a 2-year period. Because our model period is one year, wetransform the 2-year transition matrices to a one-year transition matrices. Table 2 displays the one-year transition of the 3 states. We can observe that theprobabilities of transiting to ‘low’ are monotonically decreasing in age. On theother hand, the probabilities of transiting to ‘high’ in general show an opposite pattern across age groups. In the computation, we linearly interpolate thetransition probabilities so that transition matrices change smoothly over the lifecycle.
The transition probabilities of remaining in the same states over the life cycle
are shown in Figure 6. The probability of staying in “low” (the line ‘low-low’) ismonotonically decreasing in age, while the probability of remaining in “high”(the line ‘high-high’) is monotonically increasing after age 26. In Figure 7, we
display the unconditional probabilities of being in the three expenditure statesover the life cycle, implied by the transition matrices.

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4.4.2 Medical Expenditure States
The “Estimates of National Medical Care Expenditures,” which is publishedby the Ministry of Health, Labor, and Welfare of Japan, provides the data of
average medical expenditures by age. For our calibration, we need the expenditure shares of the three states, low (bottom 50% individuals), middle (next40%) and high (top 10%), in each age. According to Kan and Suzuki (2005),
which provides the information of average expenditure shares of 10 quantiles(unconditional on age) from 1996 to 1998, we can calculate the average sharesof the three expenditure states in total medical expenditure. We find that thebottom 50% in the distribution (“low”) only contributes 7.1% of total medical
expenditure, the next 40% of the distribution (“middle”) contributes 38.1% of
total medical expenditure, and the top 10% people’s share of total medical expenditure is as high as 54.8%. We assume that the expenditure shares of thethree states are stable across age, and then can compute the medical expenditures of the three states for each age group with the latest (2007) data from the“Estimates of National Medical Care Expenditures.” The estimated results arepresented in Table 3.
We also linearly interpolate the medical expenditures so that the medical
expenditures change smoothly over the life-cycle. Figure 8 shows the estimatedmedical expenditures of the three states from age 20 to 100.
In the model, we normalize the medical expenditure x j (h ) to match the ag
gregate medical expenditure-output ratio X/Y, where X = ( x ) dΦ( s), with thedata. We set X/Y as 7.1% in the initial stationary state. Because the aggregate
medical expenditure-output ratio increases by year, we determined the target
from trend of X/Y after 2000. In the final stationary state and transition paths,
X/Y is endogenously determined since both output Y and the price of medicalcare q change in the experiments.

4.5 Wage shock process
We approximate the labor productivity shock z by AR(1) process:ln z j+1 = λ ln z j + ε j .
It is difficult to estimate stochastic hourly wage process without micro dataon earnings and hours worked. It is very restricted to use such micro data ofJapanese labor market. We use the estimates by Abe and Yamada (2009), who
14estimate the income process of Japanese households from the National Surveyof Family Income and Expenditure, as a target of calibration for income risks.
As labor supply in our model is endogenous, the corresponding income inequality is also endogenously determined. We set the skill shock parameters{λ, σ2ε } to replicate Japanese income inequality from our model. We approximate the AR(1) process by finite Markov chain from Tauchen (1986)’s method.
We calibrate average labor productivity by age {η j } from the Basic Survey
on Wage Structure (Chingin Kozo Kihon Tokei Tyosa), which is compiled by
the Ministry of Health, Labour, and Welfare. Following the method proposed
by Hansen (1993), we compute hourly wage of each age group as in Table 5.5

4.6 Health Care, Tax, and Social Security System
4.6.1 Price of Medical Expenditure
We focus on two issues that increase tax burden: aging population and increasing per capita costs of medical care. The medical care cost, which is captured by q, should change from the initial state corresponding to 2010 and isheld constant after 2050. Following Attanasio, Kitao, and Violante (2008), we
assume that the health care inflation rate is 0.6% per year.6 Then, the price of
medical care increases about 27% in 40 years. Therefore, we set initial price of
medical care to be one, q2010 = 1, and set final price at q2050 = 1.27.
4.6.2 Health Care System
All citizens are covered by the UHI. Financial sources of medical cost consistof three components: (i) premium, (ii) government subsidy, and (iii) out-ofpocket expenses. The premium covers only a half of total medical expenditure.
The average out-of-pocket expense rate is about 15%. The co-insurance rate,
1 − ω j , is 30% under age 70, 20% between 70 and 74, and 10% over 75. As thefraction of individuals who have bad health status increases by age, the average

5 For details, see also Braun et al. (2007).
6 This number is deflated by both a general inflation rate and a macroeconomic growth rate.

Thus, the relative price of medical care cost increases by 0.6% per year. In Japan, from Iwamoto(2006), the medical care cost is estimated to increase 2% per year. However, the number is not
adjusted by the macroeconomic growth rate and an average TFP growth rate is estimated to beabout 1% in Japan (İmrohoroğlu and Sudo, 2010). Therefore, the estimated health care inflation
rate in the US may not differ significantly that in Japan.

15

out-of-pocket rate is less than 30%. The remaining cost of the UHI is financedby the government’s general revenue.
4.6.3 Tax System
We use linear tax rate because our focus in this paper is to quantify the burden of future health care system, and it is difficult to interpret the result if thetax code is nonlinear. Notice that the labor tax rate τ l balances the government’s budget constraint in equation (7). Currently, the consumption tax rateτ c in Japan is set at 5%.
We calibrate exogenously determined public expenditure G to match G/Y in
the model with the data. For example, Government expenditure in 2008 is 84.7
trillion yen, which includes expenditures for public pension and medical carethat amount 23.6 trillion yen. Thus, the government expenditure without social
security related expenditure is 62.1 trillion yen. As nominal GDP in Japan isabout 492 trillion yen, and the G/Y is about 12.43% in 2008. We use the average
G/Y from 2000 to 2008, 12.5%.
4.6.4 Social Security System
The payroll tax rate of social security system in 2010 is 16.054%. Thus, we
set the payroll tax rate τ ss in the initial steady state to be 16.054%. As a part ofsocial security reforms, the payroll tax rate plans to increase by 0.354% per year
and stop to increase in 2018. The payroll tax rate in the final steady state is set at18.3%. Under the transition paths, we use the increasing tax rates. In all cases,
the replacement rate φ is endogenously determined in the model.
4.6.5 Social InsuranceSocial assistance (lower bound of consumption) c is set at 10% of average
consumption, which prevents a situation that individuals with low wealth andhit by large medical expenditure shocks could have negative consumption.

16

5 Analysis
5.1 Impacts of population aging and increased medical cost
We use data from 2010 to set the initial values for the state variables. We
investigate the impact of population aging and medical cost increases keeping
all other things unchanged.
We first compare tax burdens in a steady state economy with the 2010 demographic structure and in economies with a population structure as projected
in 2050. We assume that 2010 is the initial steady state. The benchmark model
economy is calibrated to match the tax burden, the medical care cost, the capitaloutput ratio, population structure and some aggregate variables of Japanese
economy in 2010 (the first column of Table 6). The government expenditure
to GDP ratio is fixed at 12.5% as in 2010 by assumption. We also assume thatthe policy of government’s subsidy to UHI is fixed: 25% of the total UHI cost(ψ = 0.25); the policy of UHI co-insurance rate ω is assumed to be fixed, too.
The remaining cost of the UHI is fully financed by the premium (a labor tax) in
new steady states. The following scenarios are investigated:
Population aging
In 2050, the elderly dependency ratio is forecasted to approach 80%. Obviously
there will be an increase in the UHI cost due to the demographic change – there
are more old people, who demand more medical care, but fewer tax/premium
payers. In this case, we assume that the de-trended medical price q stays constant from 2010 to 2050 (i.e. the growth of medical price is equal to the aggregate growth along the balanced growth path). Although we assume thatgovernment’s subsidy policy to UHI (the share of the UHI cost) is fixed, thegovernment still needs additional revenue to finance the share of the increased
UHI cost. We assume the government would adjust payroll tax to ensure that
it is able to finance the subsidy – 25% of the total UHI cost. We simulate theeconomy in a steady state with the 2050 population age structure and the above
assumptions. The simulation result is presented in the third column of Table
6. The higher UHI cost requires increases in the payroll tax rate and the premium tax. The additional UHI cost in 2050 accounts for a 8.8% labor tax burden(including both payroll tax and premium tax) for young people. This figure is
likely to be the lower bound since we assume constant medical cost through
2050.
17

Aging with increased cost of medical care
If the price growth of medical care (relative to consumption good) is similar
to the US, with a 0.6% annual growth rate on top of the productivity growth,
the medical care in 2050 will be about 27% more expensive than in 2010. Taking
into account this medical price growth, the UHI in 2050 will cause an additional
13.6% tax burden on labor. The result is shown in the 4th column of Table 6.
Therefore, including the increased tax burden of social security tax, the total
payroll tax for workers will be more than 40%. Because of the high medical care
price and declined output, the medical cost output ratio is predicted to be 15.7%
in our simulation.
A counterfactual experiment, in which there is only the medical price increase without population aging, is also performed. The result is listed in thesecond column of Table 6. Only medical price growth, with a 0.6% annual
growth rate on top of the productivity growth to 2050, result in an additional
2.5% labor tax burden.

5.2 Reform of UHI policy
To reduce the tax burden on the young and to lessen the distortion on labor
supply with the aged population in 2050, we first consider following potential
UHI policy alternatives by adjusting the co-payments, which were already increased several times by the government in the past:a) Having the elderly’s (those above 70) co-payment rate adjusted to 30% as
young people’s;b) Raising up the general co-payment rate to 35%, 40%, 45%, and 50% insteadof the current 30%, and having old people’s co-payment rate the same as young
people’s.
We still assume that government subsidy share of the UHI cost is fixed asin the benchmark, 25%. The remaining cost of UHI is fully financed by thepremium tax. Government consumption to GDP ratio is fixed at 12.5%. The
government would adjust payroll tax rate to balance its budget.
In addition to tax burden, the welfare effects of the alternative UHI policies
are also evaluated. Welfare is measured by expected life time value with equilibrium distribution of all population or of the new-born. Welfare deviationfrom the steady state with the original policy is calculated by using the certainty
equivalent consumption variation (CEV) measure. Given the utility function,18

CEV for a representative agent can be expressed by the following equation:
CEV = (Vnew /Voriginal )1/[σ(1−γ)] − 1,
where Vnew is the welfare in the economy with a new policy and Voriginal is thewelfare in the original economy. The CEV based on all population (i.e. the social
average) is defined as:  1σ (1−γ)Vnew ( j, h, a, z)dΦ( j, h, a, z)
CEVall = − 1,Voriginal ( j, h, a, z) dΦ( j, h, a, z)
where Φ is the stationary distribution of population over the state variables.
The CEV based on new-born agents is defined as:  1σ (1−γ)Vnew ( j = 20, h, a, z)dΦ( j = 20, h, a, z)CEVnb =
− 1.
Voriginal ( j = 20, h, a, z) dΦ( j = 20, h, a, z)
The results of the policy experiments are presented in Table 7. We can seethat the K/Y ratio increases as the UHI co-payment rate is raised because agents
have to accumulate more precautionary savings to guard against the medical
expenditure risk by themselves, especially for their old periods.
In addition, the policy reform of increasing co-payment forces old people toshare more the medical care cost and lowers down the tax burden on young
people. Therefore, we observe significant welfare improvement of the policy
reform for the new-born (see CEV for the new-born in Table 7). Moreover, thereduction of labor tax burden will less distort labor supply and improve thewelfare. However, the higher co-payment hurts old people who face higher
medical expenditure uncertainties. The average welfare of all population would
be much smaller than the CEV of new-born households, although these are still
positive (see CEV(all population) in Table 7).

5.3 Reform of financing policy
Here we investigate alternative financing policies for the UHI with the aged
population. The current consumption tax in Japan is 5%, which is much lower
than other developed countries. Some government proposal of increasing consumption tax has attracted a lot of discussion. Therefore, we particularly focus
on consumption tax (τ c ), which can be a substitute of labor tax and less distorting labor supply by spreading the tax burden to all of the population. We investigate two potential reforms: Increasing consumption tax rate τ c to 1) 10% and19

to 2) 15%, and check the corresponding changes in steady states with the population structure in 2050. The results of the policy experiments are presented inTable 8.
Imposing a higher consumption tax to substitute the labor tax has a redistribution effect across generations: it forces old people to share more tax burden
through the consumption tax since they do not pay any kind of labor taxes, andtherefore reduces young people’s tax burden. The decrease in labor tax burden
reduces labor distortion and improves welfare. The policy also affects asset accumulation – people need to save more for their retirement to finance the pricier
consumption. So we find higher K/Y ratios in the simulation results with thepolicy experiments.
In general, the welfare effect of this financing policy reform is similar but
much smaller than that with the UHI co-payment increase. The new-born enjoy
the reform but the old do not although the overall CEV is positive.
Our finding shows that all the above policy reforms significantly improve
the welfare of the future generation with an aged population.

5.4 Decomposition of the Welfare
To have a better understanding on the welfare changes with the reforms,
we decompose CEV into a component from the change in distribution and acomponent form the change in aggregate level. The approach of welfare decomposition is similar to that in Conesa et al. (2009). Table 9 presents the result.
We find that both the distribution effect and the level effect are important toaccount for the welfare changes caused by the above policy reforms. However,
the welfare improvements are mainly contributed by the changes in consumption. There is a welfare gain stemming from the leisure distribution over thelife-cycle, but a loss caused by the level change in leisure offsets the gain.

5.5 Transition – welfare implication for current generation
In the above we compare welfare changes in different steady states. However, the cost/benefit along with the transition is not considered that has a direct welfare implication to the current generation, who politically determines
the policy.
Now we take into account the transitional cost for better understanding thewelfare impacts of the alternative polices on the current generation (who lives20

in 2010). We assume that from the first steady state in 2010, a new policy is implemented in 2011 unexpectedly, and the economy transits to reach the second
steady state in 2200. Between 2010 and 2050, the survival probabilities and population growth rates, as well as the population age structure evolve according
to the population forecast; after 2050, the demographic factors stop changing
and the economy converges to the new steady state in 2200. We compute theequilibrium transitional path between the two steady states. The approach that
we use here is similar to Nishiyama and Smetters (2005).7
To calculate the welfare along the transition, we need one additional statevariable t, the time period (year). The state vector s now becomes: s = ( j, h, a, z, t).
We calculate CEV by age for those who live in 2010 to understand the impactsof potential policy reforms on the current generation. The CEV of individuals
with age j = jx in 2010 is defined as:  1
σ ( 1 − γ)V new (s| j = jx , t = 2010)dΦ(s | j = jx , t = 2010)
CEVjx , 2010 =  original− 1,
V(s| j = jx , t = 2010)dΦ( s| j = jx , t = 2010)
where Φ( s| j = jx , t = 2010) is the stationary distribution of population over thestate space conditional on age jx in 2010.
We perform a transition analysis for the following three potential policy reforms:
1) a sudden UHI policy change – increasing the elderly’s UHI co-payment rate
to 30% as young people’s from current 20% for age 70-74 and from 10% for age
75 and above in 2011;2) a gradual UHI policy change – increasing the elderly’s co-payment rate by
1% per year until it reaches 30% as in policy 1;3) a sudden financing policy reform – increasing consumption tax to 10% fromthe current 5% in 2011;4) a gradual financing policy reform – increasing consumption tax to 10% fromthe current 5% by 1% per year.
The welfare changes by age and health status of individuals living in 2010
are presented by “Policy 1”, “Policy 2”, “Policy 3”, “Policy 4” in Figures 9 – 15.
Figures 9 – 12 present welfare changes by age and health status for each policy
separately. Figures 13 – 15 compare welfare changes with the four policies fordifferent health status individuals separately.
We first discuss the implication from Policy 1. With the implementation of
Policy 1, we find that, the majority of the current population will encounter7 See the computational details in the appendix.

21

welfare losses. Particularly, the result suggests that older individuals would encounter higher losses under the reforms, while younger individuals, especiallythose younger than 35, might have welfare gains. As in the above steady statecomparison, those reforms require old individuals to share more medical carecost than under the current policy and relieve young individuals’ tax burden.
We also observe that for those aged 65 and above, the welfare losses arelarge under Policy 1 – on average above 8% of their life time consumptions
except those very old and close to the terminal age. The large loss is because
first, the elderly face higher medical shocks and so the increased co-payment
hurts them more. Second, most importantly, because the new policy is assumed
to be implemented unexpectedly right after 2010, those already retired have nochance to prepare (i.e. accumulate more assets) for the sudden out-of-pocket
medical cost increase during the time when they were working. The welfare
loss is severe particularly for those with bad health whose medical care cost
can be even higher than the average income (see Figures 9 and 15). In thiscase, the unexpected 10-20% additional co-payments would largely reduce theconsumption of those unprepared, retired and high-medical-risk people. The
new policy on UHI co-payments in fact forces unhealthy/old people to share
more medical cost than healthy people.
As mentioned above, a potential tax tool, consumption tax, is currently considering by the Japanese government. We find that Policy 3, a consumption
tax increase that can reduce labor tax rate by a similar proportion in the steadystate as with Policy 1, has a much milder impact on current old individuals(Figure 11) although they will still encounter welfare losses. Because the tax
is only imposed on non-medical-care consumption, the redistribution between
the high-medical-risk and the low-medical-risk is much smaller than the UHI
co-payment reform. Hence the welfare changes with different health statuses
are not significantly different.
To prevent the disadvantages of a sudden UHI policy reform as discussed
above for the Policy 1, we further consider a gradual reform of the UHI policy(Policy 2): the elderly’s co-payment rates are increased by one percentage point
per year until they reach 30% as that for the young. We find that the welfare(CEV) pattern over age with this gradual reform policy is similar to the consumption tax reform (Policy 3). We also find that a gradual reform on increasing
consumption tax (Policy 4) has a welfare effect similar to Policy 3 (Figure 11).
The results suggest that a consumption tax reform might be more politically
implementable than a one-time full change in UHI co-payment, which hurts the22current elderly largely, although both reduce tax burden for young people. An
alternative reform of the UHI policy is a gradual co-payment increase, whichallows more time for individuals to prepare for the policy change and preventthe sudden shock to the current old people, can be also considered. A gradualreform on consumption tax does not differ much from an immediate increase.

5.6 Discussion: the political dilemma
Our above analysis indicates a difficulty of the reforms – the majority of
the current population will suffer from the reforms even though the welfare
improvement for the future generation is significant. To more clearly understand the support of the reforms from the current generation, we calculate theagreement rates with each of the policies discussed in the transition analysis.
We assume that if an individual expects a welfare improvement along with thetransition of a reform policy, the individual will agree with the reform. Figure
16 presents the agreement rate by age with each reform policy for the current
generation (who lives in 2010).
We find that for Policy 1, an increase in the elderly’s UHI co-payments,
young individuals with age 31 and below are very supportive but none ofindividuals aged 40 and above will support the reform. The agreement rateof Policy 2, which increases the elderly’s UHI co-payments gradually, is evenlower, because it loses some support from young individuals although it has amilder negative impact on old individuals. The support to Policy 3 is the highest among the four potential reforms. Most of the individuals aged below 40
will agree with the reform. In addition, the negative impact on old/unhealthy
persons is much smaller than Policy 1.

6 Concluding Remarks
We construct a general equilibrium life-cycle economy to study the impactof an aging population (an increased dependency ratio and increased per capita
medical expenditures) on household’s work and savings behavior, as well as on
aggregate output and welfare. We find that with real medical care price fixedat the 2010 level, UHI will still become more costly in 2050 because of the fast
population aging that leads to an additional 8.8% labor income tax burden on
the young. If the real medical care price grows as in the US at a rate 0.6% on
top of the productivity growth annually, the extra tax burden on the young
23

will be 13.6% of labor income. We also evaluate various policy alternatives designed to lessen the negative impact of aging on the economy. Welfare analysis
is performed. In particular, taking 2010 as an initial starting point, we calculate
the transition path predicted by our model as the population structure changes
and medical costs increase, using values for 2050 to construct a terminal steadystate. We particularly discuss potential reforms on UHI co-payment policy andgovernment financing policy. We find that reform policies of a UHI co-payment
increase and of a consumption tax increase both are able to reduce the tax burden on young people. However, the two reform policies have opposite redistribution effects between the young and the old (as well as between the healthy
and the unhealthy). Our findings suggest that a consumption tax reform or a
gradual reform of UHI co-payments have a much milder negative impact on oldpeople. However, the total agreement rate of the gradual reform from the current generation is even lower than a one-time full change in UHI co-payments
because it loses the support form the young age. A consumption tax reform
has a highest agreement rate, although still lower than 50%, and might be morepolitically implementable.

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[28] Krueger, D. and A. Ludwig (2007), “On the Consequences of Demographic
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27

Table 1: Medical cost over age groups (2007)

Age Group
Total
Under 65
0-14
14-44
45-64
Over 65
Over 70
Over 75

Per person
medical cost
(1,000 yen)
267.2
163.4
134.6
103.3
261.6
646.1
722.2
794.2

As of
total average
(%)
–
61.15
50.37
38.66
97.90
241.80270.28297.23

Source: Estimates of National Medical Expenditure, Japan28

Table 2: Transition of medical expenditure
age: 0–17
low
middlehighage: 18–35
low
middlehighage: 36–45
low
middlehighage: 46–55
low
middlehighage: 56–
low
middlehighlow
0.82800.23090.0400low
0.77840.30870.1137low
0.7566
0.28170.0603low
0.73320.21300.0399low
0.69070.18180.0131

middle0.16150.72620.3914
middle0.20400.6356
0.3284
middle0.22320.65230.3452
middle0.23900.68880.2443
middle0.28490.68500.1531high
0.01050.04290.5686high
0.0176
0.05570.5579high0.0202
0.06600.5945high
0.02780.09820.7158high
0.02440.13320.8338

Note: Calculation based on Kan and Suzuki (2005).

29

Table 3: Medical Care Expenditure Per Capita 2007 (Unit: 1,000 yen)Agemean expenditure
0-4
219.0
5-9
112.6
10 - 1479.5
15 - 1965.1
20 - 24
72.6
25 - 2996.9
30 - 34111.9
35 - 39120.6
40 - 44136.0
45 - 49164.5
50 - 54214.1
55 - 59293.4
60 - 64356.0
65 - 69455.4
70 - 74590.1
75 - 79696.1
80 - 84809.5
Over 85
943.0
average267.2

low middle high31.1
208.4 1200.8
16.0
107.2
617.4
11.3
75.7
435.9
9.2
62.0
357.0
10.3
69.1
398.1
13.8
92.2
531.3
15.9
106.5
613.6
17.1
114.8
661.3
19.3
129.4
745.7
23.4
156.6
902.0
30.4
203.8 1174.0
41.7
279.2 1608.8
50.6
338.8 1952.1
64.7
433.4 2497.1
83.8
561.6 3235.7
98.8
662.5 3816.9
114.9 770.4 4438.7
133.9 897.5 5170.8
37.9
254.3 1465.1

Source: “Estimates of National Medical Expenditure”
and authors’ calculation.

30

Parameters
Discount factor
Intertemporal elasticity of substitution
Share of labor supply
Capital share
Depreciation rate
Persistence of labor productivity shock
Std. dev. of labor productivity shock
Government share of UHI
Price of medical expenditure

β
γ
σ
α
δ
λ
σε
ψ
q

Table 4: Parameters of the Model

Age

ηj

Age

ηj

20–24
25–29
30–34
35–39
40–44

0.545
0.718
0.884
1.030
1.149

45–49
50–54
55–59
60–64
60–64

1.243
1.271
1.130
0.770
0.654

Table 5: Age-Efficiency Profile

31

Value
0.98
2.0
0.33
0.377
0.08
0.98
0.09
0.25
{1, 1.27}

Table 6: The impact of population aging/increased medical cost on UHI

Age structure
Medical price
Change in K
Change in L
K/Y
X/Y
G/Y
Tax burden
Social security tax
Consumption tax
Capital tax
Payroll tax
Premium
Total labor tax burden
Increased UHI burden(ratio to labor income)Benchmark Only Price
2010
2010
q=1
q = 1.27
0.00%-1.47%
0.00%-0.18%
2.520
2.500
7.1%
9.1%
12.5%
12.5%

Only Aging Aging & Price
2050
2050
q=1
q = 1.27-0.52%-4.67%-16.63%-17.23%
2.813
2.752
12.1%
15.7%
12.5%
12.5%

16.1%
5.0%
39.8%
6.2%
6.9%
13.1%

16.1%
5.0%
39.8%
6.9%
8.9%
15.7%

18.3%
5.0%
39.8%
9.7%
12.3%
22.0%

18.3%
5.0%
39.8%
10.9%
15.9%
26.8%

-

2.5%

8.8%

13.6%

Note: K/Y – capital output ratio; X/Y – medical cost output ratio;
G/Y – government expenditure-output ratio.

32

Table 7: Alternative UHI policies in 2050– steady state comparison

Change in K
Change in L
K/Y
X/Y
G/Y
Tax burden
Social security tax
Consumption tax
Capital tax
Payroll tax
Premium
Total labor tax burden
Welfare comparison
CEV(new-born, h =good)
CEV(new-born, h =fair)
CEV(new-born, h =bad)
CEV(all population)

Current
UHI policy reform
systemCo-payment rate
q = 1.27
30%
35%
40%
45%
50%
0.00%
14.00% 19.10% 24.35% 29.86% 35.31%
0.00%
2.01% 2.79% 3.52% 4.21% 4.90%
2.752
2.949
3.016
3.085
3.156
3.225
15.7%
14.8% 14.5% 14.2% 13.9% 13.6%
12.4%
12.4% 12.4% 12.4% 12.4% 12.4%
18.3%
5.0%
39.8%
10.9%
15.9%
26.8%

18.3%
5.0%
39.8%
10.8%
12.5%
23.2%

18.3
5.0%
39.8%
10.8%
11.3%
22.1%

0.00%
0.00%
0.00%
0.00%

9.68%
9.70%
9.76%
1.44%

12.65% 15.50% 18.21% 20.84%
12.66% 15.49% 18.19% 20.80%
12.66% 15.45% 18.09% 20.66%
2.14% 2.72% 3.13% 3.63%

33

18.3%
5.0%
39.8%
10.8%
10.2%
21.0%

18.3%
5.0%
39.8%
10.8%
9.2%
20.0%

18.3%
5.0%
39.8%
10.9%
8.2%
19.1%

Table 8: Financing policies in 2050– steady state comparison

Change in K
Change in L
K/Y
X/Y
G/Y
Tax burden
Social security tax
Consumption tax
Capital tax
Payroll tax
Premium
Total labor tax burden
Welfare comparison
CEV(new-born, h =good)
CEV(new-born, h =fair)
CEV(new-born, h =bad)
CEV(all population)

Current
systemτ c = 5%
0.00%
0.00%
2.752
15.7%
12.4%

Financing policy reform
Consumption tax rate τ c
10%
15%
5.20%
10.26%
1.07%
1.99%
2.821
2.889
15.3%
15.0%
12.4%
12.4%

18.3%
5.0%
39.8%
10.9%
15.9%
26.8%

18.3%
10.0%
39.8%
6.8%
15.5%
22.3%

18.3%
15.0%
39.8%
2.7%
15.1%
17.9%

0.00%
0.00%
0.00%
0.00%

3.68%
3.69%
3.74%
1.19%

7.02%
7.04%
7.12%
2.14%

34

Table 9: Decomposition of welfare change

UHI policy reform
Co-payment rate

Financingpolicy τ c

30%
35%
40%
45%
50%
10%
15%
CEV (total)
9.69% 12.65% 15.49% 18.19% 20.82% 3.69% 7.03%
Level
5.01% 6.82% 8.57% 10.19% 11.87% 1.73% 3.30%
Only c
6.00% 8.30% 10.55% 12.67% 14.90% 2.49% 4.73%
Only n-0.93% -1.38% -1.81% -2.21% -2.66% -0.74% -1.37%
Distribution 4.80% 5.91% 6.95% 7.94% 8.80% 1.97% 3.71%
Only c
3.36% 4.06% 4.71% 5.33% 5.86% 1.49% 2.80%
Only n
1.42% 1.82% 2.21% 2.58% 2.91% 0.48% 0.89%

35

70

Fraction of population (%)

60
50
40
30
20
0−14
15−64
65+

10
0

2010

2020

2030
Year

2040

2050

Figure 1: Japan’s population structure 2005 – 2055

36

100
90

Total dependency ratio
Elderly dependency ratio

Dependency ratio (%)

80
70
60
50
40
30
20
10
1980

1990

2000

2010

2020
Year

2030

2040

2050

Figure 2: Japan’s dependency ratios 1980 – 2055

37

Medical Cost/National Income (%)

10
9
8
7
6
5
4
1985

1990

1995
Year

2000

2005

Figure 3: Trend of Japan’s medical care cost 1985 – 2007

38

2.5

Fraction of Population (%)

Simulated
Projected
2

1.5

1

0.5

0
20

40

60
Age

80

100

Figure 4: Actual and Simulated Population Distribution in 2010

39

2.5

Fraction of Population (%)

Simulated
Projected
2

1.5

1

0.5

0
20

40

60
Age

80

100

Figure 5: Actual and Simulated Population Distribution in 2050

40

0.95
0.9

g−g
f−f
b−b

Transition Prob.

0.85
0.8
0.75
0.7
0.65
0.6
0.55
20

40

60
Age

80

100

Figure 6: Transition probabilities of remaining in the same state

41

0.7

Invariant Distribution

0.6

good
fair
bad

0.5
0.4
0.3
0.2
0.1
0
20

40

60
Age

80

100

Figure 7: Invariant distribution of the medical expenditure states

42

6

Medical Expenditure (2007, yen)

6

x 10

5

good
fair
bad

4
3
2
1
0
20

40

60
Age

80

Figure 8: Medical expenditures by age in 2007

43

100

5
0

CEV (%)

−5
−10
−15
−20
−25
−30
20

good healthfair healthbad health
40

60
Age

80

100

Figure 9: Policy 1 – CEV by age and health status (transition)

44

5
0

CEV (%)

−5
−10
−15
−20
−25
−30
20

good healthfair healthbad health
40

60
Age

80

100

Figure 10: Policy 2 – CEV by age and health status (transition)

45

5
0

CEV (%)

−5
−10
−15
−20
−25
−30
20

good healthfair healthbad health
40

60
Age

80

100

Figure 11: Policy 3 – CEV by age and health status (transition)

46

5
0

CEV (%)

−5
−10
−15
−20
−25
−30
20

good healthfair healthbad health
40

60
Age

80

100

Figure 12: Policy 4 – CEV by age and health status (transition)

47

5
0

CEV (%)

−5
−10
−15
−20
−25
−30
20

Policy 1
Policy 2
Policy 3
Policy 4
40

60
Age

80

100

Figure 13: Comparison – CEV by age, good health (transition)

48

5
0

CEV (%)

−5
−10
−15
−20
−25
−30
20

Policy 1
Policy 2
Policy 3
Policy 4
40

60
Age

80

100

Figure 14: Comparison – CEV by age, fair health (transition)

49

5
0

CEV (%)

−5
−10
−15
−20
−25
−30
20

Policy 1
Policy 2
Policy 3
Policy 4
40

60
Age

80

100

Figure 15: Comparison – CEV by age, bad health (transition)

50

100
Policy 1
Policy 2
Policy 3
Policy 4

Agreement Rate (%)

80

60

40

20

0
20

40

60
Age

80

Figure 16: Agreement rates of the reform policies

51100