On the Consumption Insurance Effects of Long-term Care Insurancein Japan: Evidence from Micro Household Data * **Yasushi Iwamoto, University of Tokyo
Miki Kohara, Osaka University
Makoto Saito, Hitotsubashi University
September 2006
Abstract: Using micro-level household data in the 2001 Comprehensive Survey of the
Living Conditions of the People on Health and Welfare as compiled by the Japanese
Ministry of Health, Labor and Welfare, this paper examines how having a household
member in need of long-term nursing care can result in welfare losses measured interms of consumption. In doing so, the study evaluates the role of the public long-termcare insurance scheme implemented in Japan in April 2000. The results indicate thatwhen households included a disabled family member, household consumption net oflong-term care costs did not decrease as much as before the introduction of long-termcare insurance. When compared with the surveys conducted in 1995 and 1998, theadverse effects on consumption net of long-term care costs have became much weaker.
These findings suggest that the introduction of social insurance in 2000 helped to reduce
the welfare loss associated with having a disabled family member.
JEL classification numbers: E21, I18
Keywords: social insurance; consumption insurance; long-term care insurance*

The authors would like to thank Dae Il Kim and seminar participants at Seoul National
University for their helpful comments. This research was supported by the International
Collaboration Projects of the Economic and Social Research Institute at the Cabinet
Office, Japan. The authors accessed the micro-level data in the Comprehensive Surveyof the Living Conditions of the People on Health and Welfare with the special
permission of the Statistical Bureau of the Ministry of Internal Affairs andCommunications. Regrettably, Japanese Statistics Law does not permit the authors todisclose details of the individual dataset.
**
Correspondence to: Yasushi Iwamoto, Graduate School of Economics, University ofTokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan, E-mail: iwamoto@e.utokyo.ac.jp, phone: +81-3-5841-5641, fax: +81-3-5841-5521.

1. Introduction
Employing a micro-level household dataset compiled by the Ministry of Health,
Labor and Welfare, this paper examines how the state of having a household member
who needs long-term nursing care could result in welfare losses measured in terms of
consumption, and evaluates the role of the public long-term care (hereafter, LTC)
insurance that was implemented in Japan in April 2000.
This paper attempts to measure the welfare loss that a household would suffer fromhaving a disabled or bedridden household member in terms of the effects on household
consumption. There are two basic channels whereby a household member in need oflong-term nursing care could affect household consumption: (1) a decline in permanent
income because of the sacrifice of earning opportunities in order to take care of thedisabled, and (2) a decrease in household consumption net of LTC costs as a result ofexpenditure on the uninsured costs associated with having a disabled member.
The first channel works as follows. A person who cares for a disabled family
member at home may sacrifice a job opportunity. For example, a person who lives witha bedridden parent may give up a position which may then force workers to move to adifferent location or shorten their working hours. In any case, the long-term losses inearning opportunities could certainly decrease permanent household income. The
decline in permanent income in turn lowers household consumption. The second
channel is that without an appropriate insurance instrument, household members areforced to sacrifice items of consumption (on goods or services) or withdraw theirsavings to pay uninsured LTC costs.
The above framework has a similar spirit to the literature on consumption insurance
that examines the effect of adverse health shocks on consumption. Based on the Panel
Study of Income Dynamics, Cochrane (1991) found that a loss of work hours because ofhealth problems reduced food consumption. If a household head became absent at theworkplace for more than 100 days (the probability of this event was 7.2% in the sample),consumption declined between 11% and 14%. From the 1975–1985 panel data on
families in rural areas in India, Townsend (1994) found that the percentage in the year
when an adult male was sick had no impact on consumption. Gertler and Gruber (2002)
examined panel data conducted in Indonesia and found that the impairment of theactivities of daily living (ADL) led to a significant economic loss. The impairment of-1-

basic ADL (2% in the sample) decreased consumption by 59%. The problem ofintermediate ADL (24% in the sample) decreased consumption by 14%. Gertler, Levine
and Moretti (2001) used a different dataset on Indonesian households, but obtained asimilar result. Dercon and Krishnan (2000) regarded individual nutritional status(weight divided by squared height) as a proxy for consumption, and explored rural
Ethiopian household data. They did not find that nutrition was affected by unpredictable
losses of working days. On the other hand, Wagstaff (2005) used the same index as anindicator of health status. Using panel data on Vietnamese households, Wagstaff (2005)
found that a decrease in the average nutritional status of household members by one
standard deviation reduced food consumption by 1.2% and non-food consumption by
2.9%. 1
Our empirical investigation takes into consideration the introduction of the public
LTC insurance scheme in April 2000. 2 The Japanese Government introduced thissystem in compensation for the lack of private insurance. 3 The public LTC insurance

1

Most studies on consumption insurance have used household data in developing
countries. Chetty and Looney (forthcoming) caution that the welfare consequences ofconsumption smoothing may be different between developing and developed countries.
Using panel data on households in Indonesia and the United States, they found thatIndonesian households used costly methods to smooth consumption. Even whenhouseholds smooth consumption with limited financial instruments in developing
countries, households may still suffer from adverse shocks, and the provision of social
insurance may help to improve welfare substantially. As an alternative approach, using
US micro-level data (the National Long-Term Care Survey), Sloan, Hoerger, and Picone(1996) examined the effects of LTC needs on non-housing wealth rather thanconsumption and found negative, though less significant, wealth impacts.
2
See Campbell and Ikegami (2002) and Mitchell, Piggott and Shimizutani (2004) for a
detailed explanation of Japanese LTC insurance. Geraedts, Heller and Harrington (2000)
carefully document the German social insurance approach to LTC services.
3
Several studies, including Pauly (1990), Cutler (1993), and Cochrane (1995), haveprovided a number of explanations for why private insurance fails to cover the risk of
LTC [see Norton (2000) for a more detailed review). For example, in respect to the
supply-side, it is extremely difficult to calculate expenses of long-term nursing careaccurately. It is also difficult to forecast future technical innovation properly in medical
technology. In regard to the demand side, it is difficult for individuals to evaluate theirown risk of the need for LTC. Individuals who underestimate this necessity have lessincentive to buy insurance. They may also substitute the informal care provided byhousehold members for the purchase of insurance. When the demand for insurance is
not strong for those reasons, a private insurance company would not offer any plan at areasonable price. Mellor (2001), Finkelstein, McGarry and Sufi (2005) and Brown and-2-scheme aims to provide disabled family members with financial assistance as follows.
To start with, enrollees in the public LTC insurance scheme are all residents aged 40
years or more. Each municipal government is responsible for operating the public LTC
insurance scheme in its own territory. To obtain benefits, a person has to be examined
concerning the status of disability by an expert committee. The government sets thecategorization procedure based on various kinds of information. When a person iscertified as being in need of LTC services, an independent care manager develops aservice plan for him/her.
The introduction of the public LTC insurance scheme changed the way that LTC
services are delivered and financed in Japan. 4 As these services had hitherto been
financed by municipal governments’ general budgets, the supply of services tended tobe limited. 5 The public LTC insurance scheme covers long-term nursing care both athome and in nursing care facilities. Under the public LTC insurance scheme, theservices are provided through a quasi-market mechanism. Once a person is certified as
needing LTC services, he/she can purchase the necessary services with the help of the
LTC insurance and can freely choose a provider. Because profit-making organizations
are permitted to enter homecare markets, the number of LTC service providers has
dramatically expanded.

Finkelstein (forthcoming) empirically tested some of these theoretical implications.
4
The coinsurance rule in public LTC insurance is that a beneficiary pays 10 percent of
total costs. One-half of the entire insurance benefits is financed with insurance
premiums. The premiums paid by those aged 65 years and over are, in principle,
withheld from public pension benefits, while persons aged under 65 years pay
premiums along with their health insurance. The premiums of employees areproportional to their earnings. The premiums for persons other than employees are
divided into proportional and fixed parts: the former is partly related to income andpartly to asset holdings. At the aggregate level, the remaining half-share of benefits isfinanced with subsidies from national, prefectural, and municipal governments.
5
Municipal governments (major or ordinance-designated cities, ordinary cities, towns,
or villages) offered their own long-term nursing assistance for the disabled elderly even
before the central government introduced LTC insurance in 2000. Accordingly, there
were substantial regional differences in the extent to which a municipal government
provided long-term nursing assistance: some municipal governments offered generous
assistance for the disabled, while others local governments did not. It at first appears
that we could exploit this information to identify the institutional effects on
consumption insurance. As described later, however, the inability to access any detailed
information concerning examinees’ places of residence for privacy reasons prevented us
from exploiting regional differences in public assistance availability.
-3-Thus, the extent to which the public LTC insurance scheme can absorb the household
risk associated with severely disabled family members, who to a great extent had notbeen sufficiently insured prior to its introduction, should be subject to a rigorous
empirical study. To the best of our knowledge, there are few studies that empiricallyexamine the possible effects of public LTC insurance, although several countries havealready introduced similar schemes. 6 Our paper attempts to offer a rigorous empiricalassessment of the public LTC insurance scheme introduced in Japan. Such empiricalevidence may then be informative for other countries considering this kind of social
insurance.
As a result of our focus on the effects on household consumption as a welfare
measure, we can evaluate the impact of the introduction of this type of social insurance
more precisely. For example, social insurance is expected to absorb the risk of LTC
needs. On the other hand, as the public LTC insurance scheme does not provide income
support, the loss of earnings opportunity may not be covered. Hence, the public LTC
insurance scheme differs sharply from other social insurance programs designed toinsure income risks directly. 7 To highlight this aspect of the public LTC insurance
scheme, we carefully separate the effects of having severely disabled members onhousehold permanent income from the effect on household consumption. In ourempirical framework, if the social insurance scheme absorbs the risk of LTC needs, its
effect on consumption is not statistically significant after controlling for permanent
income. 8 If the effect on consumption is significant before the introduction of the public
LTC insurance scheme, but insignificant afterwards, then social insurance is found tocover an important risk not covered by the private sector.
The dataset we use is the micro-level data in the Comprehensive Survey of the Living
Conditions of the People on Health and Welfare (Kokumin Seikatsu Kiso Chosa inJapanese) (hereafter Survey of Living Conditions or SLC), which is a nationally6Gupta and Li (2004) simulated the optimal plan of purchasing long-term careinsurance.
7
Bloemen and Stancanelli (2005) and Gruber (1997) assessed the consumption
insurance effects of unemployment insurance.
8
Wagstaff (2005) found that a health shock had a negative effect on non-medical
consumption, even among households that purchased health insurance, and conjectured
that health insurance did not effectively tackle income losses. However, he did not take
into consideration the possible impact of a health condition on permanent income.
-4-

representative household survey. The SLC contains detailed information about LTC
needs and economic status every three years. As the public LTC insurance scheme wasintroduced in April 2000, we use the datasets gathered before and after this event (1998
and 2001). In addition, we compare the estimation results based on the 1998 and 2001
SLC with those derived from the 1995 SLC reported in Iwamoto, Kohara and Saito(hereafter IKS, 2001).
The remainder of this paper is organized as follows. Section 2 describes our dataset,
while Section 3 reports the estimation results and discusses the implications. Section 4
offers some concluding remarks.
2. Data Descriptions and Basic Statistics
2-1 Data Characteristics
We use the household micro-level data of the Comprehensive Survey of the Living
Conditions of the People on Health and Welfare compiled by the Ministry of Health,
Labor, and Welfare, and recognized as one of the most comprehensive governmentsponsored collections of household micro-level data. The SLC conducts a large-scale
survey every three years, when more than 30,000 households usually provide
information concerning household income and consumption together with details of thehealth conditions of household members. For estimation purposes, we employ thesurveys conducted in 1998 and 2001. In addition, the estimation results based on thesesurveys are compared with those based on the 1995 survey, which is reported in IKS.
(2001).
The SLC is well suited to the purposes of our empirical investigation. First, thislarge-scale household survey reports on several important dimensions of household
characteristics, including family structure, job status, income, financial assets, realestate and health conditions of every family member. In regard to severe healthconditions, the SLC surveys in detail whether a family member needs LTC as a result ofa physical disability, and if so, what kind of care is provided for the disabled member.
Second, given that it is a large-scale household survey, we can include a reasonable
number of households with a member in need of LTC in our sample, even though theprobability of having a severely disabled family member is extremely low in the overall
population. In this regard, unlike micro-level datasets that survey only those households-5-with disabled members, a dataset constructed from the SLC allows us to explore
differences in household behavior between families with disabled members and those
without. Third, the 1998 and 2001 surveys are conveniently timed for the purpose ofevaluating the possible welfare impacts of the public LTC insurance scheme introducedin April 2000.
For privacy reasons, we were not permitted to have access to any detailed
information concerning the location of the respondent’s residence. We could obtain,
however, the prefecture where the surveyed household resided, and the population classof the city/town/village of residence (150,000 persons or more, between 50,000 and
150,000, and 50,000 or less). Consequently, we cannot exploit the substantial
differences in the availability of social services among municipal governments observed
before the introduction of the public LTC insurance scheme in 2000.
Both the 1998 and 2001 SLC identified a particular family member residing at home
as a member in need of LTC, when he/she required nursing assistance in the following
six activities of daily living (ADL): (1) washing face and teeth, (2) changing clothes, (3)eating, (4) discharging, (5) bathing, and (6) walking. Thus, the degree of need for LTC
may be measured in terms of how many activities required nursing assistance. In
addition, the 1998 SLC classified the state of a bedridden member according to a levelfrom ‘occasionally’ through ‘sometimes’ and ‘most of the time’ to ‘completely.’ Inaddition, the 2001 SLC compiles the degree of need of LTC that is authorized under the
public LTC insurance scheme law where an independent examiner judges the state ofnursing care required ranging from Level 1 (the lightest) through to Level 5 (the mostserious) by visiting each applicant for a public LTC insurance scheme payout. Under
this classification, a member classified as Level 5 is almost equivalent to a bedridden
member.
We construct two kinds of dummy variables concerning the state of disability. One
dummy variable takes a value of one if a family member older than 40 years needs help
with at least four activities, zero otherwise. Using the 1995 SLC, which basicallyfollows the same definitions as the 1998 and 2001 SLC, IKS (2001) classify a memberin need of LTC as one who needs nursing assistance in four activities or more. The
other dummy variable takes a value of one if he/she is bedridden, zero otherwise. We
define a bedridden member as one assigned to either of the two severe states.

-6-

The SLC reports the annual household income of the previous year, the monthly
expenditure on household consumption in May of the surveyed year, and the healthcondition of family members as at the first Thursday in June of the surveyed year. For
example, the 2001 SLC reports annual income in 2000, monthly consumption
expenditure in May 2001, and the health conditions of family members as at June 7,
2001.
One potential problem associated with the timing of the survey is that eachhousehold reports its income not in the surveyed year, but in the previous year. To deal
with this issue, we construct a dummy variable for currently bedridden members foreach household, and a dummy variable for having had bedridden members for morethan one year. However, it is not possible to make such a control in constructing
dummy variables of having disabled members in need of at least four activities (adefinition of which is described below). In this regard, our estimation potentially fails to
capture the effects of disabled members on household income. Nevertheless, this aspect
does not affect the estimation results because there is no substantial difference in theestimation results using currently bedridden members and that one year before.9 For thisreason, we report the estimation results based on the current state of disabled family
members.
The SLC identifies a particular family member who is institutionalized, such as at anursing facility. 10 However, neither of the SLCs reports the health condition of
institutionalized family members. We construct a dummy variable for the presence offamily members who are in nursing facilities in order to capture the close similarity
between being nursed at home and being institutionalized.
As discussed in the introduction, we evaluate the welfare impact of having a family
member in need of LTC in terms of the loss in household consumption. When adisability shock hits a family member, extra expenses incurred in caring for the disabled
member may be financed from household savings or may be compensated for by giving

9More precisely, because of the smaller sample in the latter construction, point
estimates of the dummy variables associated with disabled members become lesssignificant because of larger standard errors.
10
The SLC also identifies family members who are hospitalized for a long period oftime but does not record their ages. It is thus impossible to construct a dummy variable
for the presence of hospitalized elderly members.
-7-

up other consumption expenses. Some family members, in particular the spouse of ahousehold head, may quit his/her current high-income job and switch to another job
with a lower commitment, thereby sacrificing lifetime income and allocating time to thecare of the disabled member at home. The combined effects of these compensating
activities are eventually reflected in changes in household consumption net of LTC
costs. The SLC also reports any uninsured expenses on LTC including extra clothes,beds, caring tools, charged care service, and uninsured medical expenses. We thus use
household consumption net of expenditure on LTC costs as a household welfare
measure.
We now make several remarks on the use of consumption as a welfare measure in thecontext of the LTC. First, consumption expenditures reflect the consumption service
available from market activities, but not from home production. For example, as a resultof having a disabled member, a family may eat more often at home than away from
home, and may reduce expenditure on consumption. A decrease in food consumption
for this reason may not necessarily be interpreted as decrease in welfare. Second, as aresult of allocating more time to LTC at home, a family may reduce time-consuming
consumption activities such as travel and sports. Once again, such a decline in
consumption may not exactly capture the increase in disutility associated with giving up
leisure time.
2-2 Basic Statistics
We use the sample of households whose household head (more precisely, the highest
income earner in the household) is an employee. A major reason for this sample
selection is that we are primarily interested in the case where healthier (and maybe
younger) household members support an elderly member in need of nursing care. 11 We
also exclude as outliers those whose household income (consumption) is four standard
deviations from the mean. As a consequence, the number of observations is 15,262 forthe 1998 SLC, and 15,542 for the 2001 SLC.

11

Our investigation may underestimate the welfare impacts of having a disabled
member because our sample excludes the much more serious case where the household
head becomes in need of nursing care.
-8-

Table 1 and Table 2 report the basic statistics for our sample comprising the 1998
and 2001 SLC. In regard to the 1998 SLC, the number of households with members inneed of nursing care for at least four disability activities is 215 observations (1.41%),
while the number of households with bedridden members is 77 observations (0.50%).
As for the 2001 SLC, the number of households with members in need of nursing care
for at least four disability activities is 419 observations (2.70%) Based on the authorized
degree of LTC required under the law governing the public LTC insurance scheme, thenumber of households with members in need of nursing care is 85 observations (0.55%)
for Level 5 (equivalent to a bedridden state).
Given the differences in the share of families with disabled members between the1998 and 2001 surveys, it may be difficult to compare directly estimations from the1998 survey with those from the 2001 survey. One possible reason is that in response to
the introduction of the public LTC insurance scheme in 2000, greater recognition may
have been given to the situation of disabled members within households, andconsequently the 2001 survey may have recognized disabled members much more
broadly than the 1998 survey.
Even in comparison with the 1995 and 1998 surveys, the former reports a smaller
share of households with disabled members than the latter. More concretely, the shareof household members with four or more disability activities is only 0.81% in the 1995
SLC, but 1.41% in the 1998 SLC. The share of households with bedridden members is
0.38% in the 1995, but 0.50% in the 1998 SLC. More general recognition might havebeen paid to the state of the disabled even before the public LTC insurance scheme was
implemented in 2000, or the number of members in need of nursing care might haveindeed increased with population aging in Japan.
In both the 1998 SLC and the 2001 SLC, the share of a family in which an adultchild supports his/her disabled parents is the largest among households with disabled
members. For example, in the 1998 SLC (the 2001 SLC), the proportion of households
in which a spouse’s bedridden parent is supported is 35.4% (36.3%), the proportion ofhouseholds in which a head’s bedridden parent is supported is 17.2% (24.3%), and the
proportion of households in which a bedridden spouse is supported is 30.2% (27.2%).
The number of households that have disabled members at nursing facilities is 46(0.30%) in the 1998 SLC, and 93 (0.60%) in the 2001 SLC. According to IKS (2001),-9-

on the other hand, 72 such households make up 0.47% of the entire sample in the 1995
SLC.
Table 2 compares the averages of representative household characteristics such as
income and consumption net of LTC costs in households with disabled members and in
those without. According to this table, the average income (or consumption) of theformer is not necessarily inferior to the latter. As far as the average level is concerned,
there is no direct evidence for an adverse impact of having a disabled member in termsof household income and consumption. However, note that in families with disabled
members, the age of the household head is more than 10 years older than in families
without a disabled member. This finding appears reasonable in that parents ofhousehold heads and their spouses are more likely to need LTC when they get older.
The numbers of household members and workers are larger in families with disabled
members than in those without them. Household consumption may be heavily
influenced by these household characteristics. Section 3 explores in detail how thepresence of a disabled member could have welfare impacts after controlling for otherpossible effects of household characteristics on income and consumption.
3. Statistical Specification and Estimation Results
3-1 Statistical Specification
Because we have cross-sectional data at particular points of time (1998 and 2001)
and not panel data, we cannot estimate a structural form based on dynamic optimization,rather only a reduced-form specification to evaluate the impact of having disabled
members within a family.
We construct a two-stage specification for this purpose. First, we estimate householdincome as a function of household characteristics assuming fixed effects, including adummy variable associated with disabled members, and use predicted householdincome as a proxy for the permanent income of a household in the second stage. This
first-stage estimation allows us to identify the impact of disabled members onhousehold permanent income. In the second-stage estimation, we specify household
consumption net of uninsured expenditures on LTC as a function of household
characteristics, including the household permanent income predicted by the first stage
estimation, and a dummy variable for the presence of disabled members. For the- 10 -

second-stage estimation, we add as explanatory variables several factors specific to theconsumption decision.
There are two channels, indirect and direct, through which the state of having
disabled members could yield welfare impacts in terms of consumption net of nursing
care costs. By an indirect channel, a disabled state may reduce household permanent
income, thereby lowering consumption. By the direct channel, on the other hand, given
permanent income, consumption may decline through the state of a household having
disabled members.
Our two-stage procedure is suitable for classifying the role of insuring risks causedby having disabled members. As described, the LTC insurance scheme provides in-kindbenefits for both home care and institutional care, but does not provide any cash benefit
for care provided by family members. As it is not an income support program, it does
not compensate for income losses because of a problem with disability. Therefore, the
LTC insurance scheme does not help mitigate a substantial decline in permanent incomein the first stage, but is intended to offset a decrease in consumption in the second stage.
In the first-stage estimation, the household income function is specified as:Jln yi = ∑ α j x1ij + β d i ,

(1)

j =1

where y i and x1ij denote the total income and characteristics of household i.
A set of variables of household characteristics {x1ij } includes the number ofhousehold members (in logarithms), the age of the household head and its square, thesex of the household head, whether the household head is married or single, the numberof children relative to the number of household members, the number of parents relative
to the number of household members, the number of income earners, the scale of thefirm in which the household head is employed, and a dummy variable for households
residing in a city. In addition, we include a dummy variable for the presence of disabled
members in nursing facilities so as to consider the similarity between nursing thedisabled member at home and outside the home. As mentioned earlier, although thetiming of the recording of a health condition differs from the timing of the recording ofhousehold income, such differences in recorded timing do not substantially affect the- 11 -

estimation results. In addition, d i is a dummy variable indicating the presence ofdisabled members within household i. Thus, a coefficient on d i ( β ) represents the(possibly negative) effect of the state of having disabled members on permanent income.
In the second-stage estimation, the household consumption function is specified as:Jln ci = γ (ln yi ) + ∑ λ j x2 ij + μd i ,
e

(2)

j =1

where (ln y i ) e is the household income predicted in the first-stage estimation, while ci
denotes household consumption net of nursing care costs.
Unlike the first-stage estimation, the SLC records the monthly household
consumption of May of 1998 or 2001, and there is no significant difference in thetiming of recording health conditions (in the early June) and household consumption. A
set of household characteristics adds a dummy variable of children attending a college
and living separately, and a dummy variable associated with home ownership in order
to control for possible impacts on consumption behavior.
In equation (2), the coefficient on d i ( μ ) represents the direct effect of disabled
members on household consumption. A possible dynamic effect, such as adjustment
costs or habit formation, may be captured by the coefficient on the proxy for permanent
income ( γ ) being less than one.
Throughout the two-stage estimation procedure, we assert that the state of having
disabled members is completely exogenous. Although we regress a dummy variable ofdisabled members on every possible household characteristic to explore endogenous
nature, we cannot find any systematic pattern in determining the state of having
disabled members. 12 Thus, the above identification assumption can be justified as far as
our dataset is concerned.

12

The only exception to this is that the probability of having disabled members tends tobe higher in households with more rooms and/or a larger ground area. This indicatesthat physical capacity is an important determinant in nursing disabled members at home.
- 12 -

3-2 Estimation Results
Tables 3 and 4 report the estimation results of the income and consumption functions
based on equations (1) and (2) using the 1998 and 2001 SLC datasets for both the casewith household members with at least four disability activities and the case withhousehold members bedridden for at least one year.
Before discussing the effects of the presence of disabled members, we briefly explore
the effects of other household characteristics on the estimation results based on the 1998
and 2001 SLC datasets. Most of the estimated coefficients appear to be quite reasonable.
Household income increases with age, but at a diminishing rate, while it increases with
the number of household members, but decreases with the number of children. Bothhouseholds with male and married heads and those working for larger firms or residing
in larger cities tend to earn higher incomes.
On the other hand, household consumption largely reflects household income. In
addition, consumption is influenced by student-related expenditure. A significantly
positive coefficient on the dummy variable for home ownership indicates that houses
that are owned may serve as a proxy for net household wealth. One point to be noted isthat the estimated coefficient on the dummy variable for disabled members in nursing
facilities is significantly negative in the 1998 estimation; that is, household consumption
declines by about 20% in the presence of disabled members in nursing facilities. A
similar effect is absent from the 2001 survey. We will discuss this part of the estimation
results later.
In regard to the effects of the presence of disabled members, we first discuss theestimation results using the 1998 SLC. As documented in Table 3, in terms ofhousehold income functions, the state of having disabled members yields negative
impacts on household income, although the estimates are slightly insignificant (the pvalue is 11.7% for the estimation based on members with four or more disability
activities, and 10.5% for that based on bedridden members). More concretely, the stateof having members with problems in at least four ADLs reduces household income by
5.5%, while the presence of bedridden members lowers household income by 9.0%. On
the other hand, the state of having disabled members has a significantly negative effecton household consumption. That is, the state of having members with problems in at- 13 -

least four ADLs reduces household consumption by 9.2%, while the presence of
bedridden members lowers household consumption by 7.7%.
The estimated marginal propensity to consume out of permanent income, as capturedby γ , is slightly less than 50% in both cases (45.8% and 46.1%). As suggested earlier,an estimated γ less than one may be a consequence of slow consumption adjustment
because of habit formation. Thus, as a result of the combined effect through bothindirect and direct channels, household consumption would decline by 11.7% forhouseholds with members with problems in at least four ADLs, and by 11.8% forhouseholds with bedridden members.
One caveat concerning the estimated welfare impacts of LTC is that it only considers
the case where disabled members are cared for at home and does not take into
consideration any cost associated with institutional services. As indicated, household
consumption declines by about 20% in the presence of disabled members in nursing
facilities. In this regard, the estimated welfare impact implied by the 1998 estimation
may be underestimated to some extent.
The estimation results of the 2001 SLC contrast with those of the 1998 SLC in thatthe state of having disabled members has a significantly negative impact only onhousehold income. As shown in Table 4, and in the case of members with at least four
disability activities, the state of having a disabled member results in a 22.5% decrease inhousehold income, while the state of having bedridden members reduces householdincome by 15.3%. Another difference from the 1998 estimation is that the presence of afamily member who is institutionalized has no impact on household consumption.
On the other hand, the state of having members with at least four disability activities
has little direct impact on household consumption. Consequently, the state of having
disabled members reduces household consumption only through the indirect channel.
Unlike the 1998 estimation, the coefficient on the dummy variable for disabled
members in nursing facilities is not significant. The absence of negative effects on
consumption in the second stage estimation may be interpreted as supportive evidence
for the direct effects of the public LTC insurance scheme introduced in April 2000. In
addition, one possible interpretation of the insignificant effect of institutionalized
household members is that the public insurance system may even reduce the potential
burden on those who would have even nursed disabled members outside the home.

- 14 -Given that the coefficient on predicted household income is estimated to be less than
50%, the state of having disabled members reduces household consumption by the orderof half of the estimated impact on household income. More precisely, the state withhousehold members with at least four disability activities reduces household income by22.5%, while the marginal propensity to consume out of predicted household income is41.8%. Accordingly, household consumption decreases by 9.4% as a result of theindirect effect. Similarly, in the presence of bedridden members, household
consumption decreases by 6.4% as a result of the indirect effect.
3-3 Discussion
As discussed, the state of a household having disabled members has a significantly
negative impact on household welfare in terms of a decrease in household consumption
in both the 1998 SLC and the 2001 SLC, but the pattern differs between the twodatasets. In the 1998 SLC, the state of having a disabled member has negative impacts
on both income and consumption. In the 2001 SLC, on the other hand, the state of
having disabled members has negative impacts on income, but not on consumption. As
the introduction of the public LTC insurance scheme was a nationwide policy change, awell-designed control group was not available. Although we cannot preclude thepossibility that the time series change in other factors may lead to a different
consumption insurance effect, the most significant change in the environment
surrounding a person who needs an LTC was the most likely to cause the difference.
According to IKS (2001), who employed almost the same methodology with the
1995 SLC, the state of having disabled members has significantly negative impacts on
both household income and consumption. 13 More concretely, as shown in Table A-1,
households with members with at least four disability activities significantly reduces
household income by 11.5% and household consumption by 24.3%, while the state of
having bedridden members reduces household income by 15.3% and household
13

There are a few minor differences in the construction of explanatory variables. First,
in the 1995 dataset, the dummy for a disabled member was set at one if the member had
been in care for more than six months. Unfortunately, the information about the durationof this status is not available in the 2001 dataset. Second, the dummy for a bedridden
member was set at one if the member had been bedridden for more than six months.
Third, the dummy for a college student was set at one regardless of whether or not they
lived separately from the household.
- 15 -

consumption by 33.8%. Given that the marginal propensity to consume out of predicted
household income is estimated to be 23.1% or 23.0% (much smaller than in the 1998
and 2001 data), household consumption should decline by either 27.0% or 37.3% as aresult of the combined effect through the indirect and direct channels.
These results jointly demonstrate that the introduction of the public LTC insurance
scheme in 2000 has substantially mitigated the risk faced by a household with aseverely disabled member. First, we find that after controlling for the effect ofhousehold income, the state of having disabled members still has a significantly
negative impact on household consumption in both 1995 and 1998, but little effect onhousehold consumption in 2001. That is, the public LTC insurance scheme, which was
specifically designed to mitigate consumption risk, indeed helps to absorb the risk of
LTC needs that appear at the level of household consumption.
Second, the overall impact of the state of having disabled members on household
welfare measured in terms of consumption has weakened significantly over time. As
mentioned, in the case of members with at least four disability activities, household
consumption decreases by 27.0% as a result of both the indirect and direct channels in
the year 1995. On the other hand, household consumption decreases by 11.7% throughthe indirect and direct channels in 1998, and by 9.4% and by only the indirect channel
in 2001. In the case of bedridden members, the combined effects are –37.3% in 1995, –11.8% in 1998, and –6.4% in 2001. The pattern in diminished welfare impacts of thestate of having disabled members can be justified by the introduction of the public LTC
insurance scheme law in 2000. In addition, it is consistent with the fact that municipal
governments put the public LTC system into effect by implementing its provisions
before 2000.
Third, the estimation results imply that the public LTC insurance scheme reduces therisk faced by a household that has institutionalized a disabled member in a nursing
facility. According to the 1998 analysis, having disabled members outside the homeshould cost substantially more; that is, household consumption should decrease by
about 20% when there are family members in nursing facilities. Based on the 1995
survey reported by IKS (2001), household consumption decreases slightly andinsignificantly. However, such an adverse effect on household consumption is absent
from the 2001 estimation results. One possible interpretation of the difference among- 16 -

the three sets of results is that the public insurance system may even mitigate thepotential burden of those with institutionalized disabled members. Under the prepublic
LTC insurance scheme era, the provision of institutional nursing services was part ofthe social welfare program, and fees for nursing facilities depended on the income levelof the user’s household. For middle-income earners who had institutionalized theirparents in nursing facilities, the out-of-pocket payments were burdensome. As the
public LTC insurance scheme pays 90% of total costs, this then helps to reduce thefinancial burden of middle-income households.
4. Concluding Remarks
The literature on consumption insurance has successfully revealed which kinds ofrisks are not absorbed well by informal, private or social insurance. Our paper aimed toconnect this approach to a public policy issue, by comparing the consumption insurance
effects given a fundamental change in the social insurance scheme. Employing the
micro-level household data in the 1998 and 2001 SLC compiled by the Japanese
Ministry of Health, Labor and Welfare, this paper has examined how the state of having
a household member who needs LTC results in welfare losses measured in terms of
consumption, and evaluates the role of the public LTC insurance scheme introduced in
April 2000.
Our findings are summarized as follows. First, in the 1998 SLC, the state of having
disabled members has a negative impact on both income and consumption. In the 2001
SLC, on the other hand, the state of having a disabled member has a negative impact on
income, but not on consumption. Second, the combination of indirect and direct impactsof LTC needs on household consumption has become weaker over time. Third, even theburden borne by a household with a disabled family member outside the home in 2001
is reduced to some extent.
These findings jointly demonstrate that the social insurance approach to financing
LTC costs in Japan has helped reduce the welfare loss associated with having a disabledfamily member. That is, the public LTC insurance scheme successfully absorbs the riskof expenses for a disabled member not covered by the private insurance market.
Consequently, even when households have a disabled family member, the household
consumption net of LTC costs does not decrease as much as before the introduction of
the public LTC insurance scheme.
- 17 -

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- 19 -

Table 1: Descriptive Statistics of Major Variables
Panel A: 1998 SLC

log of family consumption
log of family disposable income
log of the number of family members
the age of a household heada dummy of a male heada dummy of a married head
the number of children relative to thenumber of household members
a dummy of students living separately
the number of parents relative to thenumber of household members
a dummy of persons in nursing facilities
a dummy of firm scale (medium)a dummy of firm scale (large)
a dummy of firm scale (government office)a dummy of homeownershipa dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)the number of workers
a dummy of household members with atleast four disabled acitivities
a dummy of bedridden household members

Total Sample Number: 15262
Standard
Average
Minimum Maximum
Deviation
12.4259
0.51179.210314.4935
6.26830.64271.38637.77171.0491
0.532502.302648.2905
13.259118
95
0.8736
0.3323010.78610.41010
10.17970.22170

10.02980.17010

10.03970.108100.66670.00300.19470.26960.03020.66660.19090.3156
0.21970.05891.69580.05480.39600.44370.17120.4714
0.39300.46480.41410.23550.8486

0
0
0
0
0
0
0
0
0
1

1
1
1
1
1
1
1
1
1
7

0.01410.1179010.00500.07090

1Panel B: 2001SLC

log of family consumption
log of family disposable income
log of the number of family members
the age of a household heada dummy of a male heada dummy of a married head
the number of children relative to thenumber of household members
a dummy of students living separately
the number of parents relative to thenumber of household members
a dummy of persons in nursing facilities
a dummy of firm scale (medium)a dummy of firm scale (large)
a dummy of firm scale (government office)a dummy of homeownershipa dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)the number of workers
a dummy of household members with atleast four disabled acitivities
a dummy of bedridden household members

Total Sample Number: 15542
Standard
Average
Minimum Maximum
Deviation
12.4003
0.53379.210314.3808
6.18990.702807.75111.08400.534302.484949.7730
13.836718
101
0.87140.3347010.7766
0.4165010.17950.2219010.03700.1888010.05890.129800.75000.00600.17930.14570.10520.76270.13750.27180.21330.0892
1.82340.07710.38360.35290.30680.42540.34440.44490.40960.28510.9077

0
0
0
0
0
0
0
0
0
1

1
1
1
1
1
1
1
1
1
7

0.02700.1620010.00550.07380

1

Table 2: Long Term Care Needs and Family Characteristics
Panel A: 1998 SLC(total observations: 15262)

household members with at least four disabled activities
with the disabled

without the disabled
Mean(1) monthly household consumption (yen)(2) monthly expenditure on LTC (yen)(1) - (2)annual household income (ten thousandyen)
the age of a household head
the number of household members
the number of children
the number of workers
a dummy of homeownershipa dummy of a male heada dummy of a married heada dummy of two-generation family
the number of children relative to thenumber of household members
a dummy of students living separately
a dummy of firm scale (medium)a dummy of firm scale (large)
a dummy of firm scale (government office)a dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)

bedridden household members(Standard Deviation)

Mean

without the disabaled(Standard Deviation)

Mean

with disabled(Standard Deviation)

Mean(Standard Deviation)

284384.3(167656.9)

348093(163677.3)

284851.5(167549.4)

370129.9(188634.2)

174.3(3829.1)

47641.86(81134.7)654.4(10972.7)

38026.0(47541.1)

284210.0(167559.5)300451.2(144381.0)

284197.1(167186.2)

332103.9(176377.0)

625.9(347.3)753.5(375.0)627.0(347.5)772.8(407.9)48.1479
3.21700.77601.6927
0.66330.87240.78430.1293(13.1955)(1.4880)(1.0137)(0.8473)(0.4726)(0.3337)(0.4113)(0.3355)

58.2698
4.65580.75351.91160.90230.95810.90700.6279(13.9060)(1.4985)(1.0411)(0.9103)(0.2976)(0.2007)(0.2911)(0.4845)48.23213.22880.7756
1.69400.66530.87320.78560.1338(13.2234)(1.4930)(1.0138)(0.8475)(0.4719)(0.3327)(0.4104)(0.3404)59.8182
4.89610.80522.05190.9221
0.94810.87010.6364(15.2279)(1.5268)(1.0642)(0.9719)(0.2698)(0.2234)(0.3384)(0.4842)0.0294(0.1690)0.0558(0.2301)

0.0299(0.1703)

0.0130(0.1140)0.00270.32710.27040.01690.19110.31660.22040.0586(0.0515)(0.4692)(0.4442)(0.1288)(0.3932)(0.4652)(0.4145)(0.2349)

0.02790.26510.21400.02790.17210.24650.17210.0791(0.1651)(0.4424)(0.4111)(0.1651)(0.3783)(0.4320)(0.3783)(0.2705)

0.00280.19500.26960.03030.19100.31610.21990.0589(0.0525)(0.3962)(0.4438)(0.1714)(0.3931)(0.4650)(0.4142)(0.2354)0.05190.12990.25970.01300.16880.22080.18180.0649(0.2234)(0.3384)(0.4414)(0.1140)(0.3771)(0.4175)(0.3882)(0.2480)

Panel B: 2001SLC(Total Sample Number: 15542)

household members with at least four disabled activities
with the disabled

without the disabled
Mean(1) monthly household consumption (yen)(2) monthly expenditure on LTC (yen)(1) - (2)annual household income (ten thousandyen)
the age of a household head
the number of household members
the number of children
the number of workers
a dummy of homeownershipa dummy of a male heada dummy of a married heada dummy of two-generation family
the number of children relative to thenumber of household members
a dummy of students living separately
a dummy of firm scale (medium)a dummy of firm scale (large)
a dummy of firm scale (government office)a dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)

bedridden household members(Standard Deviation)

Mean

without the disabaled(Standard Deviation)

Mean

with disabled(Standard Deviation)

Mean(Standard Deviation)

278131.3(158930.2)

336563.2(194060.4)

279404.2(160062.7)

334705.9(184355.9)

533.8(6125.5)22357.3(38718.0)

1019.3(9208.8)

19835.9(23797.6)

277597.5(158708.1)

314205.9(188657.7)

278384.9(159534.4)

314870.0(183684.6)

594.1(346.5)610.0(352.3)594.0(346.2)685.3(404.9)49.4958
3.31910.79571.81620.75710.86980.77430.1832(13.7602)(1.5452)(1.0363)(0.9037)(0.4288)(0.3365)(0.4180)(0.3868)

59.7780
4.6516
0.69692.08590.96420.93080.85920.7399(12.8535)(1.5676)(1.0266)(1.0082)(0.1860)(0.2541)(0.3482)(0.4392)

49.7171
3.34780.79381.82170.7616
0.87110.77580.1953(13.8229)(1.5583)(1.0367)(0.9068)(0.4261)(0.3351)(0.4170)(0.3965)

59.94124.65880.64712.14120.96470.92940.91760.7176(12.5938)(1.4764)(0.9220)(1.0136)(0.1856)(0.2577)(0.2765)(0.4528)

0.0365(0.1875)

0.0549(0.2280)

0.0369(0.1885)0.0588(0.2367)

0.00470.18030.14810.10580.13970.27300.21420.0889(0.0684)(0.3844)(0.3552)(0.3076)(0.3467)(0.4455)(0.4103)(0.2847)

0.05250.1456
0.06210.08350.05730.22670.17900.1002(0.2233)(0.3531)(0.2415)(0.2770)(0.2327)(0.4192)(0.3838)(0.3007)0.00580.17940.14630.10510.13790.27200.21340.0893(0.0761)(0.3837)(0.3535)(0.3066)(0.3448)(0.4450)(0.4097)(0.2852)

0.03530.16470.03530.12940.05880.23530.18820.0824(0.1856)(0.3731)(0.1856)(0.3376)(0.2367)(0.4267)(0.3932)(0.2765)

Table 3: Estimation Results of the 1998 SLC
Panel A: with household members with at least four disabled activities
Dependent Variable: log of disposable household income
a dummy of disabled household members
log of the number of household members
the age of a household heada dummy of a male heada dummy of a married head
the number of children relative to thenumber of household members

Dependent Variable: log of household consumption net of LTC expenditures-0.0553(0.0353)
0.3405 ***(0.0206)
0.0285 ***(0.0021)0.2866 ***(0.0196)0.1291 ***(0.0196)

a dummy of disabled household members-0.3290 ***a dummy of a married head

the predicted Income
log of the number of household members
the age of a household heada dummy of a male head

(0.0348)-0.0916 ***(0.0357)
0.4577 ***(0.0297)
0.0741 ***(0.0215)
0.0025 ***(0.0004)-0.0705 ***(0.0174)
0.1065 ***(0.0160)

the number of children relative to the numberof household members

0.1845 ***a dummy of persons in nursing facilities(0.0459)-0.0454(0.0802)

a dummy of students living separately(0.0321)0.3422 ***(0.0199)

a dummy of firm scale (medium)

0.1623 ***the number of parents relative to the numberof household members

the number of parents relative to the numberof household members

0.1198 ***a dummy of firm scale (large)
a dummy of firm scale (government office)a dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)the squared age of a household head
the number of workers
constant term

(0.0107)0.3661 ***(0.0093)-0.2664 ***(0.0298)
0.0243(0.0159)
0.0427 ***(0.0120)0.0198 +(0.0123)-0.0095(0.0201)-0.0002 ***(0.0000)
0.1131 ***(0.0065)
4.0709 ***(0.0683)a dummy of persons in nursing facilities
a dummy of firm scale (medium)a dummy of firm scale (large)
a dummy of firm scale (government office)a dummy of homeownershipa dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)constant term

R-squared
F-statistics (all the coefficieints = 0)0.4184165.13 ***F-statistics (all the coefficients = 0)-0.0541(0.0399)-0.1964 **(0.0957)-0.0133(0.0111)-0.0500 ***(0.0146)
0.0759 ***(0.0230)0.0405 ***(0.0093)0.1728 ***(0.0118)
0.1128 ***(0.0105)
0.0851 ***(0.0109)
0.0085(0.0173)
9.1946 ***(0.1498)332.28 ***Panel B: with bedridden household members
Dependent Variable: log of disposable household income
a dummy of disabled household members
log of the number of household members
the age of a household heada dummy of a male heada dummy of a married head
the number of children relative to thenumber of household members

Dependent Variable: log of household consumption net of LTC expenditures-0.0898(0.0553)
0.3401 ***(0.0206)
0.0285 ***(0.0021)0.2866 ***(0.0196)0.1290 ***(0.0196)

a dummy of disabled household members-0.3284 ***a dummy of a married head

the predicted Income
log of the number of household members
the age of a household heada dummy of a male head

(0.0347)-0.0766(0.0612)0.4610 ***(0.0298)
0.0714 ***(0.0216)0.0025 ***(0.0004)-0.0716 ***(0.0175)
0.1061 ***(0.0160)

the number of parents relative to the numberof household members

0.1179 ***the number of children relative to the numberof household members

0.1875 ***a dummy of persons in nursing facilities(0.0457)-0.0425(0.0797)

a dummy of students living separately(0.0321)0.3417 ***(0.0200)

a dummy of firm scale (medium)

0.1624 ***the number of parents relative to the numberof household members-0.0634 +a dummy of firm scale (large)
a dummy of firm scale (government)a dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)the squared age of a household head
the number of workers
constant term

(0.0107)0.3663 ***(0.0093)-0.2663 ***(0.0298)
0.0243(0.0159)
0.0426 ***(0.0120)0.0199 +(0.0123)-0.0096(0.0201)-0.0002 ***(0.0000)
0.1133 ***(0.0065)
4.0709 ***(0.0683)a dummy of persons in nursing facilities
a dummy of firm scale (medium)a dummy of firm scale (large)
a dummy of firm scale (government)a dummy of homeownershipa dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)constant term

R-squared
F-statistics (all the coefficieints = 0)0.4184165.13 ***Notes
1. The number of observations is 15,262.
2. *, **, *** indicates 10%, 5%, and 1% significance levels respectively.
3. The number in a parenthesis is a robust standard error.

F-statistics (all the coefficients = 0)(0.0398)-0.1984 **(0.0953)-0.0138(0.0111)-0.0511 ***(0.0146)
0.0772 ***(0.0230)0.0409 ***(0.0093)0.1723 ***(0.0118)
0.1124 ***(0.0105)
0.0852 ***(0.0109)
0.0083(0.0173)
9.1801 ***(0.1500)
331.69 ***Table 4: Estimation Results of the 2001 SLC
Panel A: with household members with at least four disabled activities
Dependent Variable: log of disposable household income
a dummy of disabled household members
log of the number of household members
the age of a household heada dummy of a male heada dummy of a married head
the number of children relative to thenumber of household members

Dependent Variable: log of household consumption net of LTC expenditures-0.2248 ***(0.0326)0.2645 ***(0.0225)
0.0320 ***(0.0023)
0.2782 ***(0.0221)0.1858 ***(0.0203)a dummy of disabled household members-0.1796 ***a dummy of a married head

the predicted Income
log of the number of household members
the age of a household heada dummy of a male head

(0.0409)0.0295(0.0283)
0.4181 ***(0.0273)
0.1072 ***(0.0197)0.0015 ***(0.0005)-0.0543 ***(0.0177)
0.0983 ***(0.0161)

the number of parents relative to thenumber of household members

0.1993 ***the number of children relative to thenumber of household members

0.1436 ***a dummy of persons in nursing facilities(0.0470)0.0759(0.0701)

a dummy of students living separately(0.0307)0.3384 ***(0.0195)

a dummy of firm scale (medium)0.1829 ***the number of parents relative to the numberof household members

0.0518a dummy of firm scale (large)
a dummy of firm scale (government office)a dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)the squared age of a household head
the number of workers
constant term

(0.0120)0.3476 ***(0.0129)0.5050 ***(0.0133)
0.0058(0.0190)0.0523 ***(0.0129)0.0383 ***(0.0136)-0.0068(0.0180)-0.0002 ***(0.0000)
0.1194 ***(0.0070)
3.7613 ***(0.0710)a dummy of persons in nursing facilities
a dummy of firm scale (medium)a dummy of firm scale (large)
a dummy of firm scale (government office)a dummy of homeownershipa dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)constant term

R-squared
F-statistics (all the coefficieints = 0)0.3609124.35 ***F-statistics (all the coefficients = 0)(0.0362)0.0187(0.0531)-0.0230 **(0.0116)-0.0388 ***(0.0153)-0.0714 ***(0.0189)0.0795 ***(0.0107)0.1966 ***(0.0128)
0.1077 ***(0.0105)
0.0625 ***(0.0112)0.0296 **(0.0145)9.4321 ***(0.1311)318.24 ***Panel B: with bedridden household members
Dependent Variable: log of disposable household income
a dummy of disabled household members
log of the number of household members
the age of a household heada dummy of a male heada dummy of a married head
the number of children relative to thenumber of household members

Dependent Variable: log of household consumption net of LTC expenditures-0.1526 ***(0.0546)0.2556 ***(0.0225)
0.0325 ***(0.0023)
0.2782 ***(0.0221)0.1863 ***(0.0204)

a dummy of disabled household members-0.1677 ***a dummy of a married head

the predicted Income
log of the number of household members
the age of a household heada dummy of a male head

(0.0410)0.0450(0.0418)
0.4169 ***(0.0268)
0.1080 ***(0.0195)
0.0016 ***(0.0004)-0.0538 ***(0.0176)
0.0982 ***(0.0161)

the number of children relative to thenumber of household members

0.1427 ***a dummy of persons in nursing facilities(0.0468)
0.0466(0.0698)

a dummy of students living separately(0.0305)
0.3383 ***(0.0195)

a dummy of firm scale (medium)0.1835 ***the number of parents relative to the numberof household members

0.0546the number of parents relative to thenumber of household members

0.1651 ***a dummy of firm scale (large)
a dummy of firm scale (government)a dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)the squared age of a household head
the number of workers
constant term

(0.0120)0.3492 ***(0.0129)0.5060 ***(0.0133)
0.0064(0.0190)0.0516 ***(0.0129)0.0388 ***(0.0136)-0.0064(0.0181)-0.0002 ***(0.0000)
0.1217 ***(0.0070)
3.7513 ***(0.0712)a dummy of persons in nursing facilities
a dummy of firm scale (medium)a dummy of firm scale (large)
a dummy of firm scale (government)a dummy of homeownershipa dummy of city scale (metropolitan)a dummy of city scale (large)
a dummy of city scale (medium)a dummy of city scale (small)constant term

R-squared
F-statistics (all the coefficieints = 0)0.3588123.55 ***Notes
1. The number of observations is 15542.
2. *, **, *** indicates 10%, 5%, and 1% significance levels respectively.
3. The number in a parenthesis is a robust standard error.

F-statistics (all the coefficients = 0)(0.0358)
0.0211(0.0535)-0.0229 **(0.0116)-0.0386 ***(0.0152)-0.0711 ***(0.0188)0.0800 ***(0.0107)0.1967 ***(0.0128)
0.1078 ***(0.0105)
0.0625 ***(0.0112)0.0296 **(0.0145)9.4371 ***(0.1294)317.67 ***Table A-1: Estimation Results of the 1995 SLC (Iwamoto, Kohara, and Satio, 2001)
Panel A: with household members with at least four disabled activities
Dependent Variable: log of disposable household income
dummy of disabled household members
log of the number of household members
the age of a household head
dummy of a male head
dummy of a married head
the number of children relative to thenumber of household members-0.1149 ***(0.0424)
0.1937 ***(0.0187)
0.0442 ***(0.0019)0.2627 ***(0.0155)
0.1207 ***(0.0161)-0.0949 ***Dependent Variable: log of household consumption net of LTC expenditures
dummy of disabled household members
the predicted Income
log of the number of household members
the age of a household head
dummy of a male head
dummy of a married head

(0.0339)-0.2429 ***(0.0460)
0.2311 ***(0.0178)0.2320 ***(0.0200)
0.0038 ***(0.0004)-0.0355 **(0.0175)0.1358 ***(0.0171)

the number of parents relative to the numberof household members-0.4260 ***the number of children relative to thenumber of household members-0.0750 **dummy of firm scale (medium)(0.0480)
0.2126 ***(0.0099)

a dummy of students(0.0348)0.1549 ***(0.0113)dummy of firm scale (large)

0.4058 ***the number of parents relative to the numberof household members-0.0197

the squared age of a household head
the number of workers
constant term

(0.0093)-0.0004 ***(0.0000)
0.2701 ***(0.0053)3.8045 ***(0.0655)

dummy of persons in nursing facilities
dummy of firm scale (medium)dummy of firm scale (large)
constant term

R-squared
F-statistics (all the coefficieints = 0)0.4723244.01 ***F-statistics (all the coefficieints = 0)(0.0490)-0.0121(0.0592)
0.0387 ***(0.0115)
0.0574 ***(0.0125)
1.1933 ***(0.0883)372.67 ***Panel B: with bedridden household members
Dependent Variable: log of disposable household income
dummy of disabled household members
log of the number of household members
the age of a household head
dummy of a male head
dummy of a married head
the number of children relative to thenumber of household members-0.1534 **(0.0613)0.1940 ***(0.0187)
0.0443 ***(0.0019)0.2670 ***(0.0155)
0.1208 ***(0.0161)-0.0961 ***Dependent Variable: log of household consumption net of LTC expenditures
dummy of disabled household members
the predicted Income
log of the number of household members
the age of a household head
dummy of a male head
dummy of a married head

(0.0339)-0.2280 ***(0.0665)0.2299 ***(0.0178)
0.2332 ***(0.0200)
0.0039 ***(0.0004)-0.0349 **(0.0175)0.1354 ***(0.0171)

the number of children relative to thenumber of household members-0.0777 **dummy of firm scale (medium)(0.0478)
0.2125 ***(0.0099)

a dummy of students(0.0348)0.1545 ***(0.0113)dummy of firm scale (large)

0.4056 ***the number of parents relative to the numberof household members

the number of parents relative to the numberof household members-0.4326 ***the squared age of a household head
the number of workers
constant term

(0.0093)-0.0004 ***(0.0000)
0.2700 ***(0.0099)
3.7694 ***(0.0668)

dummy of persons in nursing facilities
dummy of firm scale (medium)dummy of firm scale (large)
constant term

R-squared
F-statistics (all the coefficieints = 0)0.4703243.97 ***Notes
1. The number of observations is 15,325.
2. *, **, *** indicates 10%, 5%, and 1% significance levels respectively.

F-statistics (all the coefficieints = 0)-0.0204(0.0488)-0.0206(0.0592)
0.0385 ***(0.0115)
0.0579 ***(0.0125)
1.1996 ***(0.0883)
373.11 ***