consumption insurance between japanese households
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Consumption insurance between JapanesehouseholdsMiki KoharaPublished online: 05 Oct 2010.
To cite this article: Miki Kohara (2001) Consumption insurance between Japanese households, Applied Economics,33:6, 791-800, DOI: 10.1080/00036840121946
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Consumption insurance between Japanese
households
MIKI KOHARA
National Graduate Institute for Policy Studies, 2-2 Wakamatsu-cho , Shinjuku, Tokyo,
162-8677, Japan
e-mail: [email protected]
This paper examines the implication of the full insurance hypothesis and diŒerences
in its applicability across groups of households in Japan. Using a rare Japanese
individual panel data set called the Japanese Panel Survey of Consumption, the
paper ® rst shows that the full insurance hypothesis is strongly rejected for the coun-
try as a whole. The paper further shows that the rich as well as the poor, and also
college graduates as well as non-college graduates cannot insure their consumptionagainst income shocks. In sharp contrast, urban residents can pool income shocks
completely, whereas rural residents cannot. Rural residents suŒer from income risks
more seriously than urban residents in Japan.
I . INTRODUCTION
There has been recent interest in the empirical investigation
of the hypothesis that households insure their consumption
against income uncertainty by means including risk sharing
and risk pooling. If individuals can achieve full insurance
within a country, change in an individual’s consumption
level is aŒected only by aggregate shocks and not by indi-
vidual income shocks. As a result, the consumption growth
rates should be equal among individuals in that country
and should be independent of individual income growth
rates.
Although it is hard to believe that all the people in a
country can access complete markets of the securities for
all the future possible states and completely avoid any
risks, some households might succeed in consuming the
optimal amount which they had planned even if they
faced serious income shocks. This raises the following ques-
tions: are there any groups who live in the world of full
insurance? If there are, what kinds of groups are they? The
goal of this paper is to verify the existence of insured
groups in Japan.
A great deal of empirical work has investigated the full
insurance implications and mostly rejected the hypothesis.
Cochrane (1991) partly and McCarthy (1995) strongly
reject the full insurance hypothesis for households in the
USA, using the Panel Survey of Income Dynamics (PSID).
Developing the analysis of full insurance for the entire
country, a few papers have investigated the existence of
consumption insurance within explicit and implicit groups
in the USA. McCarthy (1995) ® nds evidence supporting
full insurance for households with high wealth holdings.
He explains that rich households obtain enough savings
or borrowings to ® nance their consumption as their income
declines. As another example, Hayashi et al. (1996) show
that they cannot ® nd full insurance within a family, which
is the risk sharing between parents’ households and their
children’s households, using the PSID data.
In sharp contrast, there have been very few empirical
studies on consumption insurance for Japanese house-
holds. This is because few individual panel data sets have
been available in Japan. The published paper which comes
close to a full insurance test for Japan is Wincoop (1995)
who investigates risk sharing between Japanese prefectures.
He shows a low correlation between consumption and
income volatilities, using Japanese prefectural panel data,
and suggests that there might be risk sharing among pre-
fectures. Kohara (1997) has tested full insurance between
Japanese prefectures, using prefectural data similar to
Wincoop (1995) but applying a more direct method to
test for full insurance. Unlike Wincoop (1995), Kohara
(1997) strongly rejects full insurance between Japanese
Applied Economics ISSN 0003± 6846 print/ISSN 1466± 4283 online # 2001 Taylor & Francis Ltd
http://www.tandf.co.uk/journals
Applied Economics, 2001, 33, 791 ± 800
791
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prefectures. However, when prefectural level data are used,
an implicit but strong assumption that the full insurance
theory is applicable among individual households within a
given prefecture is imposed. This aggregation assumption
seems inappropriate. Attanatio and Davis (1996) shows
that a large speci® cation error rises when this aggregate
assumption is incorrectly imposed. To avoid this problem,
it is necessary to use panel data on households which do
not require this assumption of within-prefecture insurance.
One of the main contributions of this paper is to test full
insurance for the ® rst time using Japanese individual panel
data set. The data used in the paper are from the Japanese
Panel Survey of Consumption (JPSC, Shohiseikatsu nikan-
suru panel chosa in Japanese), which are rare panel data in
Japan.1 The use of the JPSC also contributes to comple-
menting the results on full insurance found in the USA,
since the JPSC contains a comprehensive concept of con-
sumption although PSID, which is used in most of the past
studies in the USA, reports only food consumption.
Another contribution of this paper is to verify the existence
of insured and uninsured groups in Japan. The veri® cation
is conducted by comparing the implications of full in-
surance between two sub-sample groups such as rich and
poor groups, college graduates and non-college graduate
groups, and urban and rural residential groups. The ver-
i® cation of insured and uninsured groups is important
since diŒerentials in insurance among groups in a country
can have diŒerent implications, for example, on welfare or
developments in the country. The uninsured group should
be assisted by the government’ s redistribution policy.
The main ® ndings of this paper are summarized as fol-
lows. When the test of full insurance is conducted for the
country as a whole, the paper strongly rejects the hypoth-
esis. As for the diŒerence in the full insurance implication
between rich and poor groups, it is found that the rich as
well as the poor cannot insure consumption against in-
come shocks, which is totally diŒerent from the result
McCarthy (1995) shows for the USA. At the same time,
college graduates as well as non-college graduates cannot
avoid the impact of income shocks on consumption. In
contrast, it is found that urban residents can insure fully
against income shocks, whereas rural residents cannot.
Further investigation shows that this urban± rural diŒer-
ence remains even after controlling for wealth diŒerences
and education diŒerences between urban and rural groups.
The next section reviews the theoretical implications of
the full insurance hypothesis in the literature to date. This
section also explains how to verify the existence of insuredand uninsured groups in Japan. Section III introduces the
data used and presents the regression results. It includes a
detailed discussion of the reasons for diŒerentials betweeninsured and uninsured groups. The ® nal section presents
some conclusions. The details of the data are given in the
data appendix.
II . THEORETICAL IMPLICATIONS
Full insurance
We ® rst illustrate the test implication of full insurance.
Under full insurance, households can access able contin-
gent claims for every possible state. Trading those contin-
gent claims, they can attain the optimal consumption theyhad planned initially, when state, st, is realized in period t.
Let p…st† be the price of a contingent claim for st in the
initial period. Suppose that there are S possible states in the
world, and that agents live for T periods. The optimal
consumption plan is derived from the household’s maximi-
zation of a time separable intertemporal utility functionsuch as:
T
tˆ1
1
1 ‡ »
t S
stˆ1
º…st†u…ci…st†; ¯i…st†† …1†
subject to:
T
tˆ1
S
stˆ1
p…st†ci…st† ˆT
tˆ1
S
stˆ1
p…st†ei…st† …2†
where » is the time preference rate, º…st† is the probability
of the state, both of which are identical over all agents,
u…c; ¯† is a single period utility function that depends onconsumption, c, and a preference shift parameter, ¯, and
ei…st† is agent i’ s exogenous income and transfers.
The ® rst order condition for consumption of agent i at
time t is:
1
1 ‡ »
t
uc…cit; ¯it† ˆ ¶i ¢ pt
ºt
…3†
where ¶i is a Lagrange multiplier for agent i’ s budget con-straint given by Equation 2. A subscript t simpli® es the
description of variables conditional on the state, st.
Dividing the ® rst order condition (Equation 3) at t ‡ 1
by the ® rst order condition at t, we obtain
1
1 ‡ »¢uc…cit‡1; ¯it‡1†
uc…cit; ¯it†ˆ
pt‡1=ºt‡1
pt=ºt
…4†
This states that the change in consumption for household i
from time t to t ‡ 1 should be proportional to the aggre-gate change in the economy, …pt‡1=ºt‡1†=…pt=ºt†, and to the
change in his preference shifts, but not be proportional to
the change in individual incomes. Since the aggregate
change in the world is identical over agents, Equation 4implies that under full insurance, consumption changes
792 M. Kohara
1Although there exists another household panel data called Family Income and Expenditure Survey which surveys the same households
every months for six months, it suŒers from strict limitations on its use.
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are identical over agents after controlling for individual
preference shifts.In order to derive the speci® c empirical models, a single
period utility function is further de® ned as a power func-
tion with a constant relative risk aversion parameter
® and a multiplicative preference shift ¯it, u…cit; ¯it† ˆ¯it…cit†1¡®=1 ¡ ®. Under null hypothesis of full insurance,individual consumption and individual income should be
independent. Adding the change in individual income,
ln…yit‡1=yit†, into the log of Equation 4 using a speci® ed
utility function, the estimated equation becomes:
lncit‡1
cit
ˆ ¬0
·t‡1
·t
‡ ¬1 ln¯it‡1
¯it
‡ lnyit‡1
yit
‡ uit‡1 …5†
where uit‡1 is an error term that includes unobservedpreference shifts and consumption measurement errors.
The term ·t‡1=·t summarizes the aggregate changes in
the economy, which is written in terms of p and º in
Equation 4. A time dummy or aggregate consumption
change can be used for this change. The term ln¯it‡1=¯it
describes a shift of a household’ s preference. The exact
variables for the preference shifts are speci® ed in the data
appendix. If the individual income change is cross-
sectionally independent of the error term in the estimatedEquation 5, it has no eŒects on the growth rate of con-
sumption under full insurance: ˆ 0. The alternative
hypothesis is no full insurance for the economy as a
whole: 6ˆ 0.
Insured and uninsured groups
Rejection of the null of full insurance for the country as a
whole does not always mean that there are no households
living under full insurance in the country. Some households
may hold insurance against various kinds of income risksand succeed in smoothing consumption. For a group of
these households, it can be found that full insurance
applies. That is, there exists a diŒerence in full insurance
between the group of households who are expected to be
insured and the group of the remaining households.Tests of full insurance for split groups was ® rst con-
ducted by McCarthy (1995) when he examined the diŒer-
ence between groups of households with high and low
wealth holdings (hereafter, referred to as rich and poor
groups) in the USA. Applying his analysis, the present
paper attempts to ® nd diŒerences in insurance betweenvarious groups, and specify insured and uninsured groups
in Japan. The speci® c regression equation is:
lncijt‡1
cijt
ˆ ¬0j ‡ ¬1j ln¯ijt‡1
¯ijt
‡ j lnyijt‡1
yijt
‡ uijt‡1
…6†
j ˆ
j1 if a household is categorized in a possibly
insured groupj2 if a household is categorized in a reference
group
The null of full insurance, j ˆ 0, is tested against no full
insurance, j 6ˆ 0, for the groups j1 and j2 separately. If
insured and uninsured groups are split correctly, the null
hypothesis would be accepted for group j1 but not for j2.
When the null is rejected in both groups, the degree ofcompleteness of full insurance is further compared between
the two groups, comparing the estimates of the two coe� -
cients on income change, j1 and j2; since the coe� cients
indicate how sensitive consumption changes are to income
changes.
The speci® c groups to be examined are rich and poorgroups, college graduates and non-college graduates
groups, and urban and rural residential groups. Since
rich households may be more capable of buying insurances
and/or borrowing money for income losses, one expects to
accept the full insurance implication for a rich group butnot for a poor group. This is the result actually found in the
USA by McCarthy (1995). The education one has attained
may also be correlated to the capability and tendency of
buying insurance. King and Leape (1987) demonstrate the
tendency that more educated people have more informa-tion on insurance so that they tend to insure against risks
more completely. If this was true in Japan, one would ® nd
the applicability of full insurance theory for the households
with longer periods of education. A diŒerence in insurance
may also arise between urban and rural groups for geogra-
phical reasons. What makes the urban and rural diŒerent isdiscussed later when the regression results are discussed.
III . DATA AND THE RESULTS
Data
This paper uses the JPSC, conducted by the Institute for
Household Economy in Japan. The survey started in 1993,
and the 1993 and 1994 waves are currently available. Thesample consists of married and unmarried women aged
between 24 and 34 in 1993. The survey asks married
women about their family members as well as themselves.
In this paper, the sample is limited to the married women.
This is because the test of a relationship between consump-tion and income for single women could be biased;
although Japanese single young women mostly live with
their parents and often live on parents’ income, the survey
does not ask the single women about their parents’ income
or consumption. The total number of married women is
1002. After eliminating observations with insu� cientresponses relating to all the variables required in the regres-
sions, the sample is reduced to 577.
Consumption insurance 793
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794 M. Kohara
Tab
le1.
Mea
ns
and
standard
dev
iati
ons
of
the
vari
able
s
Sp
lit
gro
ups
No
n-c
olleg
eC
olleg
eR
ura
lU
rban
Full
sam
ple
Th
ep
oor
Th
eri
chgra
duate
sgra
duate
sre
sid
ents
resi
den
ts
Th
eaver
age
of:
Con
sum
pti
on
1993
19.7
5(7
.27)
19.5
5(7
.45)
19.8
5(7
.18)
18.9
6(6
.87)
20.4
8(7
.56)
19.6
0(7
.27)
20.2
8(7
.29)
Con
sum
pti
on
1994
20.9
1(8
.6)
20.0
6(7
.77)
21.3
3(9
.11)
20.1
9(8
.05)
21.5
7(9
.23)
20.4
1(8
.26)
22.6
6(9
.97)
Co
nsu
mp
tio
ngro
wth
rate
s0.0
44
(0.4
)0.0
17
(0.4
)0.0
57
(0.3
98)
0.0
47
(0.4
06)
0.0
40
(0.3
93)
0.0
29
(0.4
09)
0.0
95
(0.3
55)
Inco
me
1993
30.1
2(1
5.0
6)
29.5
9(1
6.1
9)
30.3
8(1
4.4
9)
29.7
5(1
7.7
8)
30.4
5(1
2.0
5)
29.8
6(1
6.3
4)
31.0
3(9
.19)
Inco
me
1994
31.3
0(1
4.9
7)
29.8
6(9
.38)
32.0
1(1
7.0
3)
30.4
4(1
3.9
4)
32.0
9(1
5.8
3)
31.0
2(1
6.0
6)
32.2
8(1
0.1
8)
Inco
me
gro
wth
rate
s0.0
41
(0.3
1)
0.0
23
(0.3
66)
0.0
49
(0.2
84)
0.0
43
(0.3
18)
0.0
39
(0.3
1)
0.0
42
(0.3
36)
0.0
35
(0.2
15)
Co
rrel
ati
on
bet
wee
nin
com
ean
dco
nsu
mp
tion
gro
wth
rate
s0.1
52
0.1
99
0.1
21
0.1
39
0.1
64
0.1
66
0.0
74
Nu
mber
of
sam
ple
577
191
386
277
300
450
127
Note
s:T
he
unit
sfo
rco
nsu
mp
tion
an
din
com
eare
10
tho
usa
nd
yen
.G
row
thra
tes
are
inp
erce
nta
ges
;A
ge
isth
eaver
age
are
of
the
wif
eand
the
hu
sban
d;S
tan
dard
dev
iati
on
sare
inpare
nth
eses
.
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The details of the data used in the following regressions are
summarized in data appendix. Table 1 presents the means
and standard deviations of consumption and income. For
the entire sample, the average monthly consumption and
income are about 200 and 310 thousand yen, respectively.
Although the sample ages are not exactly same, the Family
Income and Expenditure Survey (Kakei chosa in Japanese)
shows for the age group from 25 to 34, average consump-
tion and income are 250 and 360 thousand yen, respect-
ively, while for Basic Survey on the Life of the People
(Kokumin Seikatsu Kiso chosa in Japanese) for the age
group from 30 to 39, the averages are 240 and 370 thou-
sand yen, respectively. The averages in the JPSC are smal-
ler probably because the sample in the JPSC is younger and
the sample used in this paper excludes rich single women.
Compared to the poor, the rich attain higher consump-
tion and income both in levels and growth rates. The fact
that the correlation of consumption and income is much
smaller for the rich than for the poor may suggest that the
rich can pool income shocks more successfully. As
expected, the average income for college graduates is
higher than for non-college graduates. The consumption
and income growth rates, however, are almost the same
between college graduates and the others. Also, the corre-
lation rate is not very diŒerent compared to the diŒerences
in the other groups. This leads one to expect that there is
no diŒerence in the full insurance implication between edu-
cation groups. Urban residents earn and consume more on
average than rural residents. The correlation between con-
sumption and income growth rates is much smaller for
urban residents than for rural residents, so one might expect
that full insurance is possibly attained in the urban group.
The results
Full insurance. First the full insurance implication for the
country as a whole is tested by estimating Equation 5 by
ordinary least squares (OLS).2 The results are shown in
Table 2. The coe� cient on income change, , is focused
on which shows the per centage change in consumption
as income changes by one per cent. The coe� cient of is
0.237 and is signi® cantly diŒerent from zero at the 1%
signi® cance level. Hence, the full insurance hypothesis is
rejected. The estimated coe� cient is a little bit larger
than that in the United States, which is about 0.18 in the
literature to date.
Instead of actual income changes, the paper also
attempts to use the changes in unemployment status’
which is a variable indicating whether or not either the
husband or the wife in a family `became unemployed’.
The results, however, are unchanged: the coe� cient on
the changes in unemployment status is negative and signif-
icantly diŒerent from zero at the 10% signi® cance level.This shows that consumption expenditure would be
reduced when someone in a family became unemployed
and that the full insurance implication is rejected. The
result, however, may be biased since there are few `hus-
bands’ who were unemployed in either 1993 or 1994.
Thus, the change in unemployment status principallyre¯ ects changes in the unemployment status of wives. The
eŒect of a wife being unemployed (or employed) on her
household’s expenditure seems diŒerent from the eŒect of
husband being unemployed (or employed). It is often
pointed out that the wife’ s income is just pocket money:it is not the main income which her household live on but
rather an additional income source to the main income of
her husband. If this is true, the wife’ s becoming unem-
ployed does not aŒect the household’s consumption ser-
iously, making the result look suggestive for the nullhypothesis of full insurance. Thus, the change in unem-
ployment status might not be a good proxy for income
shocks. Hence, any results using the index of changes in
unemployed status will not be reported in the following
regressions.
Insured and uninsured groups. The study will next investi-gate the diŒerence in full insurance between groups. First
of all, Table 3a shows the results for rich and poor
Consumption insurance 795
2If the error term in the regressed equation is correlated to the change in individual income, the instrumental variable (IV) estimation
should be used. This paper, however, uses OLS, because su� cient instruments for individual income cannot be found. This is probablybecause the number of the observations used in this paper is quite limited both in terms of the cross section and time. The use ofinstrumental variable estimation is left as topic for future research.
Table 2. Test of full insurance for the entire country
Regression of consumption growth
Estimated coe� cient of:Constant 0.273*
(0.151)Age 70.006
(0.005)Family needs 70.151
(0.121)Child 70.032Parents 70.085**
(0.038)Income 0.196***
(0.052)
r-squared 0.038Sample number 577
Notes: Standard errors are in parentheses; The dependent variableis the Consumption growth rates (the change in logarithms ofconsumption). Income is also taken as the change in logarithms.Details of the variables are described in the appendix, and thename of the variables are explained in the footnote of Table 1;Asterisks means that coe� cients are signi® cantly diŒerent fromzero at the 10% level (*), 5% level (**) and 1% level (***).
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796 M. Kohara
Tab
le3.
Insu
red
and
unin
sure
dgro
ups:
regre
ssio
ns
of
consu
mpti
on
gro
wth
and
test
sof
diV
eren
tials
bet
wee
ngro
ups
Tab
le3a
Table
3b
Tab
le3c
Po
or
Ric
hN
on
-coll
ege
Co
lleg
eR
ura
lU
rban
gro
up
gro
up
gra
du
ate
sgra
duate
sgro
up
gro
up
Est
imate
dco
e�ci
ent
of:
Co
nst
ant
70.1
74
0.4
67**
0.2
98
0.2
18
0.3
56**
0.0
26
(0.2
73)
(0.1
89)
(0.2
28)
(0.2
28)
(0.1
78)
(0.2
79)
Age
0.0
04
70.0
11*
70.0
07
70.0
04
70.0
08
0.0
01
(0.0
08)
(0.0
06)
(0.0
06)
(0.0
07)
(0.0
05)
(0.0
09)
Fam
ily
nee
ds
70.1
97
0.1
25
70.1
83
70.1
18
70.1
43
70.2
92
(0.1
79)
(0.1
69)
(0.1
82)
(0.1
66)
(0.1
32)
(0.3
09)
Ch
ild
0.1
13
70.0
59
70.0
12
70.0
52
70.0
45
0.0
30
(0.1
24)
(0.0
64)
(0.1
11)
(0.0
66)
(0.0
66)
(0.0
96)
Pare
nts
70.1
12
70.0
74
70.1
25**
70.0
45
70.1
16***
0.1
39*
(0.0
72)
(0.0
46)
(0.0
55)
(0.0
54)
(0.0
43)
(0.0
9)
Inco
me
0.2
18***
0.1
66**
0.1
96***
0.1
98***
0.2
06***
0.0
82
(0.0
78)
(0.0
71)
(0.0
77)
(0.0
73)
(0.0
56)
(0.1
49)
r-sq
uare
d0.0
67
0.0
35
0.0
45
0.0
35
0.0
52
0.0
31
Sam
ple
nu
mb
er191
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households. According to Table 3a, the null hypothesis of
full insurance is rejected for both rich and poor groups.
In addition, the coe� cients on income changes are the
same between two groups: the hypothesis of identical
coe� cients cannot be rejected at the 10% signi® cance
level. That is, full insurance is not attained in either the
rich group or the poor group in Japan.
This result is totally diŒerent from what McCarthy
(1995) shows for USA households, where rich households
can insure against income shocks more completely than
poor households. It is not the case in Japan that the rich
can participate more completely in insurance markets
which the poor cannot access. Also it is not the case in
Japan that rich households can pool income shocks by
using their own savings or borrowings.
Table 3b shows the results on the diŒerence between
college graduates and non-college graduates. The null
hypothesis of full insurance is rejected in both groups. In
addition, the hypothesis of identical coe� cients on income
changes between two groups cannot be rejected at the 10%
signi® cance level. Thus, no diŒerence in consumption
insurance is found between college graduates and non-col-
lege graduates. Educated people as well as less educated
people cannot insure completely their consumption against
income risks in Japan.
Table 3c presents the results on the diŒerence between
urban and rural groups. Unlike the results in Table 3a and
Table 3b, the coe� cient on income changes is signi® cantly
diŒerent from zero in rural areas at the 1% signi® cance
level, but not in urban areas at all. Thus, urban residents
insure their consumption against income risks completely,
although rural residents cannot. Rural residents suŒer
more seriously from the eŒect of income shocks on their
consumption than urban residents.
There are several explanations to account for the result.
First of all, access to insurance markets might be more
convenient in urban areas than in rural areas. The limited
access prevents rural residents from participating in insur-
ance markets. Secondly, urban residents might be relatively
rich, holding larger levels of wealth.3 It has been already
explained that the rich have a higher possibility of living
under full insurance. Although the rich and poor diŒerence
in full insurance was not statistically signi® cant in Table 3a,
the rich± poor diŒerence possibly remains between two
groups. It is true that urban residents are richer than
rural residents in Japan. The JPSC shows that the average
amount of liquid assets (saving account deposits, time
deposits, and bonds) are around 3.21 million yen in the
urban group and 2.90 million yen in the rural group.
Thirdly, it is often said that urban residents achieve higher
education levels than rural residents. According to the
JPSC, the percentage of husbands who are college gradu-
ates is 47.98% in the urban group and 31.42% in the ruralgroup. It has already been explained why college graduates
have a higher possibility of living under full insurance.
Although the educational group diŒerence did not appear
statistically signi® cant in Table 3b, the educational diŒer-
ence may still remain between two area groups, raising theurban± rural diŒerence.
The further investigation on urban± rural diVerence
If the second and/or the third explanation in the last para-
graph is true, the urban± rural diŒerence found in Table 3c
would disappear or be diminished after controlling forwealth or educational diŒerences between urban and
rural groups. The full insurance implication is re-examined
for urban and rural groups, controlling for wealth and
education diŒerences between the residential groups. The
speci® c estimated equation is:
lnciat‡1
ciat
ˆ ¬0a ‡ ¬1a ln¯iat‡1
¯iat
‡ 1a lnyiat‡1
yiat
‡ 2a lnyiat‡1
yiat
¢ Dhiat‡1 ‡ uiat‡1
a ˆu (urban residents)
r (rural residents)…7†
The diŒerence from the previous regression equation is themultiplicative term (cross term) of a household’s income
growth and a dummy variable, Dhia, which takes the value
one if household i living in area a is de® ned to be rich and
zero otherwise. That is, the coe� cient on income growth
becomes 1a ‡ 2a for the rich and 1a for the poor. If thereis no diŒerence in the insurance implications between rich
and poor households, 2a would be zero. Thus, the null
hypothesis of no diŒerence in the full insurance implication
between rich and poor households, 2a ˆ 0, is tested for
each residential group. The hypothesis of full insurance,
1a ˆ 0 and 1a ‡ 2a ˆ 0, is then tested for each residential
group. Moreover, the diŒerence between urban and rural
groups is examined, checking the diŒerence in test implica-
tions of full insurance and the estimated coe� cients, 1u
and 1r for the poor, and 1u ‡ 2u and 1r ‡ 2r for the
rich. The same method is used to control for educationaldiŒerences.
Table 4a shows the results when rich and poor diŒer-
ences are controlled for. Attention focuses on the results
for the rural group on the left half in Table 4a. The eŒect of
income changes on consumption changes for the poor is0.223 and for the rich, the sum of the coe� cient on in-
come and on cross term of income and wealth, is 0.191.
Consumption insurance 797
3The result of urban and rural diŒerence does not depend on what kinds of wealth are used. For example, the result is unchanged even if
total wealth is used including real assets such as houses and lands.
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Both values are signi® cantly diŒerent from zero at the 1%
level. In contrast, in the right half in Table 4a, the
coe� cients are 0.235 and 0.030, respectively for poor and
rich households living in urban areas. Neither of these
coe� cients are signi® cantly diŒerent from zero, supporting
the null of full insurance for both rich and poor households
in the urban group. The fact that the coe� cients for the
rural group are signi® cant but those for the urban group
are insigni® cant indicates that urban± rural diŒerences in
full insurance remains even after controlling for wealth
diŒerences. Note that the eŒect of income changes on con-
sumption changes becomes extremely small for rich house-
holds living in urban areas. Su� cient wealth holdings as
well as good access to insurance markets might make it
possible for the rich in urban areas to pool idiosyncratic
income shocks completely, and realize the amount of con-
sumption they planned.
We next attempt to control for education diŒerences
between regional groups. Table 4b shows that the coe� -
cients on the cross term of income and college dummies are
not signi® cant either in rural nor urban groups. That is, we
cannot ® nd a statistical diŒerence in consumption insur-
ance between college graduates and non-college graduates.
The coe� cients on income changes are 0.197 and 0.214 for
college graduates and non-college graduates living in rural
areas, respectively. Both coe� cients are statistically signi® -
cant from zero at the 1% level. In contrast, the respective
coe� cients are 0.302 and ¡0:064 in the urban group, and
neither is statistically signi® cant. Thus, we reemphasize the
existence of the urban± rural diŒerence even after control-
ling for education diŒerences between two area groups.
Note that the coe� cients on income changes for college
graduates in both urban and rural areas are small, which
suggests that college graduates, regardless of their location,
tend to insure consumption against idiosyncratic income
shocks.
To complete the discussion, the constraint that estimated
Equation 7 imposes is checked. The constraint is that the
coe� cients on preference shifts, ¬a1, in the estimated
Equation 7 are identical over rich and poor groups (college
graduates and non-college graduates) in a given region. If
the constraint is incorrect, for example, if an increase in
number of family members aŒects the family’s consump-
tion expenditure seriously only for the poor, the estimated
coe� cients would be biased. To test the restriction of iden-
tical coe� cients in preference shifts, one speci® cally adds,
798 M. Kohara
Table 4a. Urban vs rural controlling for the wealth diVerence Table 4b. Urban vs rural, controlling for the education diVerence
Rural Urban Rural Urbangroup group group group
Estimated coe� cient of: Estimated coe� cient of:Constant 0.360** 0.013 Constant 0.353** 0.076
(0.178) (0.28) (0.179) (0.281)Age 70.008 0.001 Age 70.008 0.000
(0.005) (0.009) (0.006) (0.009)Family needs 70.144 70.290 Family needs 70.143 70.358
(0.133) (0.31) (0.133) (0.313)Child 70.046 0.03 Child 70.044 0.027
(0.066) (0.096) (0.066) (0.096)Parents 70.116*** 0.142 Parents 70.116*** 0.148*
(0.043) (0.09) (0.043) (0.089)Income¤wealth 70.032 70.205 Income¤college 0.017 70.366
(0.113) (0.337) ((0.113) (0.309)Income 0.223*** 0.235 Income 0.197** 0.302
(0.082) (0.293) (0.080) (0.238)
r-squared 0.053 0.034 r-squred 0.052 0.042Sample number 450 127 Sample number 450 127
Test for income¤wealth ‡ incomeˆ 0’ 6.04 0.03 Test for income¤college ‡ incomeˆ 0’ 7.18 0.11(0.014) (0.861) (0.008) (0.742)
Test for the same coe� cients: F-statistics 0.44 0.37 Test for the same coe� cients: F-statistics 0.59 0.75(0.778) (0.869) (0.667) (0.586)
Notes: See the footnote in Table 2; Income¤Wealth and Income¤Education are cross terms of income growth rates multiplied by a wealthor education dummy. The wealth dummy takes the value one if a household is de® ned as rich and zero otherwise. The education dummytakes the value one if a household is grouped in the college graduates group and zero otherwise; For the tests for (in-come¤wealth ‡ income) and for (income¤college ‡ income), F-statistics and P-value are shown; The test of identical coe� cients indicatesthe test of identical coe� cients on age, family needs, child and parents over the rich and the poor (college graduates and not collegegraduates) groups. F-statistics and P-value are shown.
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to Equation 7, cross terms of preference shifts and a
dummy variable indicating a rich household (college grad-uate) and tests whether the coe� cients on the cross terms
are zero or not. If the null of identical coe� cients is
accepted, which indicates no diŒerence in the eŒects of
preference shifts on consumption changes between rich
and poor groups (college graduates and non-college grad-uates), the estimation of Equation 7 is justi® ed. On the
other hand, if the null is rejected, a correct restriction of
heterogeneous coe� cients for rich and poor groups needs
to be put separately. That is, needs to be estimated sepa-
rately in the four groups composed of a combination of
urban, rural, rich and poor.The squared sum of residuals in the regressions in Table
4a and Table 4b with and without the constraint of the
identical coe� cients on preference shifts in each residential
group is obtained. Then F-statistics of 0.44 and 0.37 in
Table 4a, and 0.44 and 0.75 in Table 4b are calculated,respectively, for the rural and urban group, accepting the
null of identical coe� cients on preference shifts both
between rich and poor groups and between college gradu-
ates and non-college graduates in both urban and rural
groups. Thus, the constraint is correct and the results ofthe regression with the constraint shown in Table 4a and 4b
are appropriate.4
IV. CONCLUSION
This paper examined the applicability of full insurance in
Japan, using the JPSC which has recently become avail-
able. It was found that the full insurance implication was
rejected for households in the country as a whole, givingthe same result as found for households in the USA by
Cochrane (1991) and McCarthy (1995).
The present paper investigated the diŒerence in the
applicability of full insurance between rich and poor house-
holds, college graduates and non-college graduates, andurban and rural residents. It was found that the rich as
well as the poor were not able to insure consumption
against idiosyncratic income shocks, which was totally dif-
ferent from the result found in the USA where the rich can
insure more su� ciently than the poor. For groups withdiŒerent education levels, it was found that the college
graduates as well as non-college graduates were not able
to insure consumption against their own income shocks.
In contrast, a serious diŒerence in consumption insur-
ance was found between rural and urban groups: full insur-
ance was supported for urban residents but not for rural
residents. Moreover, the urban± rural diŒerence remained
even after the diŒerence in wealth holdings and educationlevels between urban and rural residents was controlled for.
The extended analysis showed that the poor living in rural
areas and the non-college graduates living in rural areas
most seriously suŒer from idiosyncratic income shocks.
The results suggest that the present reallocation policywhich gives subsidies to rural areas from metropolitan
areas might be justi® ed, whereas an income reallocation
from rich households to poor households may not be sup-
ported at least in the sense of consumption insurance. It is
meaningful to take the urban and rural diŒerence seriously
when the reallocation problem in Japan is considered.One remaining problem is that the number of observa-
tions is quite limited in the regressions in the present paper,
especially after splitting the sample into various groups. As
long as alternative individual panel data are not available
in Japan, it is necessary to continue re-analysing the resultsusing the new waves of the JPSC data which will be coming
available for the next eight years.
ACKNOWLEDGEMENTS
The author is grateful to Charles Horioka, Atsushi Maki,
Colin McKenzie, Hajime Miyazaki, Kazuo Ogawa, Fumio
Hayashi, Fumio Ohtake, Makoto Saito and seminar parti-cipants at Ritsumeikan University for helpful comments.
REFERENCES
Attanatio, O. and Davis, S. (1996) Relative wage movements andthe distribution of consumption, Journal of PoliticalEconomy, 104, 1227± 62.
Cochrane, J. (1991) A simple test of consumption insurance,Journal of Political Economy, 99, 957± 76.
Hayashi, F., Altonji, J. and L. KotlikoŒ(1996) Risk sharingbetween and within families, Econometrica, 64, 261± 94.
Institute for Household Economy, Japanese Panel Survey ofConsumers, 1993 and 1994.
King, M. and Leape, J. (1987); Asset accumulation, information,and the life cycle, NBER Working Paper, No. 2392.
Kohara, M. (1997) Consumption insurance between and withinprefectures, unpublished Masters Thesis, Osaka University.
Mace, B. (1991) Full insurance in the presence of aggregate uncer-tainty, Journal of Political Economy, 99, 928± 56.
McCarthy, J. (1995) Imperfect insurance and diŒering propensi-ties to consume across households, Journal of MonetaryEconomics, 36, 301± 27.
Wincoop, E. (1995) Regional risk sharing, European EconomicReview, 37, 1545± 67.
Zeldes, S. (1989) Consumption and liquidity constraints: anempirical investigation, Journal of Political Economy, 97,305± 46.
Consumption insurance 799
4Although the constraint is accepted, the example is split into four groups and regressions conducted relaxing the constraint. It was
found that full insurance was rejected only for poor households living in rural areas and for college graduates and non-college graduatesin rural areas. That is, the urban residents, regardless of wealth and education diŒerence, and the rich rural residents can insure theirconsumption against idiosyncratic income shocks. Note, however, that the power of these tests is low, since the regressions do not use thecorrect information.
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APPENDIX
Consumption and income
For consumption, the total spending of all household
members in September, which is the surveyed month, is
used. In the regressions, its growth rates are used. For
income, the JPSC contains several measures of income,
such as annual (total) income, annual labour income and
monthly labour income. Annual (total) income and annual
labour income include taxes so that the after tax value of
income has to be calculated: the full insurance test requires
one to know how much take-home income a household can
consume. The calculation of an after tax value, however,
reduces the number of observations dramatically since the
number of the observations who respond to question about
annual tax paid in both two years is fairly limited. Hence,
the paper uses after-tax monthly income. The use of
monthly income also has a merit that the periods of earning
and consuming are matched. The mismatch is not prefer-
able because annual income may look too stable relative to
monthly consumption, which underestimates the degree of
applicability of full insurance. For the regressions, the total
income of all household members is summed and its
growth rate computed. For the index of changes in unem-
ployed status, a variable is de® ned which is one if either the
husband or the wife became unemployed from 1993 to
1994, minus one if he/she became employed from 1993 to
1994, and zero otherwise.
Preference shifts
For preference shifts (household’s characteristics), the
average age for the couple, Age, its square term, Age2,
and the household needs, FamilyNeeds which is taken as
the number of family members, are used. In addition, vari-
ables are included which possibly change the pattern of
consumption: whether or not a household has at least
one child of school-year age and whether or not a house-
hold lives with its parents. For the former group, a dummy
variable, Child, is de® ned, which is one if at least one of the
children in the family is of school-year age, and zero other-
wise, and for the latter group, we de® ne a dummy variable,
Parent which equals one if the family lives with at least one
parent, and zero otherwise. The variable Parent is included
because many elderly live with one of their children’s
households in Japan, which could change household’s con-
sumption patterns between households living with and
without the elderly. Although Age and FamilyNeeds are
taken as changes, Child and Parent are taken as levels at
the second survey year since the latter two seem aŒect
consumption path by the level themselves. Descriptive sta-
tistics on the preference shifts are summarized in the table
appendix.
Sample split
JPSC reports the amount of deposits a household holds in
saving accounts and time deposits. A liquid assets variableis computed, summing up those two values for each house-
hold and bonds. To split the sample into the rich and poor
groups, ® rst the ratio of liquid assets is computed to total
annual income. A household with the fraction over one
sixth is split into the rich group and the others into thepoor group. This follows Zeldes (1989) who uses this
split to test for the existence of borrowing constraints. To
split the sample into college graduates and others, informa-
tion is used on whether or not the husband graduated from
a university.For the urban± rural split, the JPSC categorizes the resi-
dential areas into three groups, depending on the size of the
area; the ® rst group is composed of Tokyo plus twelve
ordinance-designated cities,5 the second is composed of
so-called `cities’ , each of which is registered as a city in
the Basic Resident Registers, and the third is composedof other small towns and villages. The ® rst group is de® ned
as metropolitan or urban areas, and the second and the
third groups are merged and de® ned as small-city or
rural areas. The residents in metropolitan areas are
assigned as `urban’ residents throughout this paper sinceall of statistically metropolitan cities in Japan are located in
urban areas. Likewise, residents in small-cities could be
assigned as rural’ residents since many of small cities are
located in rural areas.6 Thus, rural residents designates
sample households living in rural areas throughout Japanand urban residents are those living in urban areas
throughout the country.
800 M. Kohara
Table appendix. Summary of households ’ characteristics used forpreference shifts over full (577) sample
Average of
Age 31.197 (3.567)Family needs 0.037 (0.137)Child 0.901 (0.299)Parent 0.241 (0.428)
Notes: Standard errors are in parentheses; Age is the average ageof the wife and the husband in 1993, family needs is the rate ofchange of the number of family members. Child shows the per-centage of households who have a child over 6 years old. Parentshows the percentage of households who live with their parents.Details of the data are contained in the data appendix.
5The twelve ordinance-designated cities are Sapporo, Sendai, Chiba, Yokohama, Kawasaki, Nagoya, Kyoto, Osaka, Kobe, Hiroshima,
Kita-Kyushu and Fukuoka.6
Note, however, that in reality some small cities are located in urban areas.
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