Discussion Paper 2017-E002

DISCUSSION PAPER SERIESOsaka University Graduate School of Medicine
Department of Health Economics and Management

What Does Sub-sectoring Household Accounts
Tell Us about Aging in Japan?

Masaaki Kawagoe
Saeko Maeda

OHEM SecretariatGraduate School of Medicine Department of Health Economics and Management
OSAKA UNIVERSITY
1-7 Yamadaoka, Suita, Osaka, 565-0871, Japan

December 2017

Abstract
A lot! Sub-sectoring household accounts is essential to understand the effects ofaging on the Japanese economy. Elderly households can fully account for an
increase in aggregate consumption expenditures in the period 1989–2009. Adecline in their saving rate, rather than age compositional effects, mainlycontributed to the decline of the aggregate household saving rate. The effects ofredistribution should also be judged based on disaggregated figures because theaverage figure shows an increase in net receipts, although no age group, but one,enjoyed the increase.

Masaaki Kawagoe
Specially Appointed Professor,
Department of Health Economics and Management
Osaka University Graduate School of Medicine
mskawag@sahs.med.osaka-u.ac.jp
Saeko Maeda
Principal Economist,
Japan Center for Economic research

Keyword： SNA, Household Accounts, Aging, Consumption, Savings,Redistribution* We would like to thank Naozumi Atoda and Yoshinosuke Hamada for encouragement anduseful comments on the earlier version of this paper. We would also like to thank Editage(www.editage.jp) for English language editing.

1. Introduction
This study divides Japan’s system of national accounts’ (SNA) household accounts intosub-sectors using microdata in order to detect the effects of aging in Japan. Althoughsub-sectoring household accounts was recommended in SNA manuals, 1 it has rarely
been attempted in studies worldwide. A notable exception in Japan is Hamada (2003),
which we updated and expanded in a series of our works.23
Sub-sectoring household accounts is essential to understand how a graying society
works in reality—in aggregate, households pay vast amounts of money on one hand,
and receive almost the same amount as pecuniary and non-pecuniary incomes on theother hand. Therefore, without sub-sectoring, it is impossible to determine theconsequences of redistribution policies, for example. Stiglitz, Sen, and Fitoussi (2010)recommended that more focus should be placed on household accounts anddistributional aspects of the SNA, which strongly encouraged our work.
The remainder of this paper is structured as follows. Section 2 explains how thedata is calculated. Section 3 shows how a decline in the saving rate of elderly
households largely accounts for the consumption expenditure growth in the two decades
up to 2009. Section 4 examines redistributive implications of changes in social security
systems. In particular, implications for the healthcare systems are further pursued insection 5. Section 6 concludes the paper.

2. Data
Sub-sectoring household accounts requires detailed information of household behaviors.
Thus, the National Survey of Family Income and Expenditure (NSFIE) is our major
information source. The survey is conducted every five years, which allows thecollection of information from 57,000 households.4 The NSFIE provides cross-sectional
information on household income and expenditure in the flow accounts, and assets andliabilities in the stock accounts. The basic strategy is to adjust individual household dataof the NSFIE, following the SNA definitions, and add them to get sub-sector figures bytype, taking into account the number of each type of households.
Although the NSFIE provides detailed information, it is still insufficient. We haveto estimate several items, which include:5 (1) various imputations, such as imputed rents

1See para. 4.151 to 4.160 and 19.9 to 19.13 in 1968 SNA Manual, and para. 4.158 to 4.165 and 24.27 to
24.31 in 1993 SNA Manual, respectively.
2
Sakai (2010), Kawagoe and Maeda (2013), Maeda and Umeda (2013), and Maeda and Kawagoe (2015).
3
Another exception is Accardo, Bellamy, Consalés, Fesseau, Le Laidier, and Raynaud. (2008), who
divided French household accounts. OECD provided guidelines for sub-sectoring (Fesseau and Le Laidier,2009).
4We have a similar survey, the Family Income and Expenditure Survey, conducted every month, with arather small sample of 9,000 households.
5See for Kawagoe and Maeda (2013) for more details.

-1-and employers’ imputed social contributions; and (2) in-kind transfers, such as medicaltreatments covered by public insurance, and public education.
Some figures in the NIFIE are, unfortunately, unreliable, so they are replaced byour estimates. First, tax and social contribution figures are estimated based on tax codesand other household data, such as revenues, marriage status, and number of children.
Second, property incomes may be downward biased because financial assets obtained
from the NSFIE severely undershoot the aggregate counterparts in the SNA Annual
Report, which is based on the Flow of Fund. To correct the underestimation, we have toresort to a top-down approach as an exception to the general principle employed here—
the bottom-up approach. To be specific, the aggregate financial assets are allocated tohouseholds on a pro rata basis, and financial incomes are calculated using the allocatedamount of assets and the assumed average rates of return on each type of financial
assets.
The above procedures bring the sum of our sub-sector estimates fairly close to theofficial SNA estimates. Unfortunately, data constraints usually disallow us from
calculating disaggregate figures, resulting in adjusted aggregates only, with no breakdowns, which are shown Column (2). Despite the aforementioned efforts, there are stillsome large gaps between the official figures and the sum of the sub-sector figures. For
example, our estimate of disposable incomes is smaller than the official counterpart by¥26.32 trillion or 8.6 percent, most of which is adjustable at the aggregate level (gap2),
but not at the disaggregate level (gap1).
Table 1 Gaps between the Official and Sub-sectoring Aggregates (Trillion yen)aggregate

subsectoring

official (1) adjusted (2)

(3)

gap 1

gap 2

gap 3

(4)=(3)-(2) (5)=(2)-(1) (6)=(3)-(1)Operating surplus and mixed income, gross

57.93

65.38

69.42

4.04

7.45

11.49

Compensation of employees, receivable

243.31226.96225.94-1.02-16.35-17.37

Property income, receivable
Primary incomes, receivable
Property income, payable

24.08

14.90

14.99

0.09

-9.18

-9.09

325.31307.24310.35

3.11-18.07-14.96

3.68

11.72

11.54

-0.18

8.04

7.86

321.64295.52298.81

3.29-26.12-22.83Social benefits other than social transfers in kind, receivable 61.83

58.85

56.93

-1.92

-2.98

-4.9

Other current transfers, receivable

15.19

15.19

15.38

0.19

00.19-46.98

Balance of primary incomes, gross418.10369.56371.12

1.56-48.54Current taxes on income, wealth, etc., payable

Secondary distribution of income, resource

24.56

24.56

26.99

2.43

02.43

Social contributions, payable

52.29

50.84

48.28

-2.56

-1.45

-4.01

Other current transfers, payable
Disposable income, grossSocial transfers in kind, receivable

15.48

15.31

15.52

0.21

-0.17

0.04

306.64278.85280.32

1.47-27.79-26.32

59.22

48.29

39.27

-9.02

-10.93-19.95365.86327.14319.60-7.54-38.72-46.26277.22257.93256.28-1.65-19.29-20.94

Saving, gross

27.39

20.92

24.04

3.12-6.47-3.35

Saving rate, gross (%)

8.93

7.50

8.60

1.1-1.43-0.33

336.44306.22295.55-10.67-30.22-40.89Adjusted disposable income, gross
Final consumption expenditure

Actual final consumption
Adjusted saving ratio (%)
Consumption of fixed capital

7.49

6.39

7.50

1.11

-1.1

0.01

20.68

17.04

16.82

-0.22

-3.64

-3.86

Disposable income, net

285.96261.81

263.501.69-24.15-22.46

Adjusted disposable income, net

345.18310.10302.78-7.32-35.08-42.4

Saving, net

6.71

3.88

7.22

3.34-2.83

0.51

Saving rate, net (%)

2.36

1.49

2.74

1.25

-0.87

0.38

Adjusted saving, net

1.95

1.26

2.39

1.13

-0.69

0.44-2-3. A Surge in Consumption by Elderly Households
Here, we provide the results of dividing the household account into 10 sub-sectors
according to age of household head. Figure 1(1) shows the results gained from fiverounds of NSFIE in the period between 1989 and 2009. The figure also presents anadditional sub-sector of elderly households with no working family members.
The age-consumption profile overall shifts up in 1994, and then, down in young
and middle-aged households. However, surprisingly, the downward shift is not observedin elderly households—their consumption level in 2009 remains virtually the same asthat in 1994. 6 The unchanged consumption level per household, together with asignificant increase in the number of these households, boosted total consumption
expenditures by the elderly households. In fact, an increase in aggregate consumption
between 1989 and 2009—¥68.1 trillion—can be almost fully accounted for by that in
the elderly households, ¥67.4 trillion, as Figure 1(2) shows.
Figure 1 Consumption expenditures by age group of household heads(1)

Consumption Expenditures by Age of Household Head(thousand yen)

6

See also Shiraki and Nakamura(2012).

-3-(2)

Decomposition of Aggregate Consumption Expenditures(billion yen)

The other side of the same coin is developments of saving rates. Figure 2 reveals
significantly different movements of saving rates, depending on the ages of household
heads. The saving rates of elderly households were higher than those of young andmiddle-aged counterparts in 1989, and thereafter, plummeted into a negative territory,
reaching a double-digit negative in 2009. 7 On the other hand, the saving rates of
middle-aged households edged up during this period.
The life cycle theory predicts that progress in aging causes a decline in aggregate
household saving rate.8 Note that the underlying assumption is that the saving rate ofelderly households is lower than that of the young and middle-aged, which was notsatisfied in the late 1980s. However, since 1999, the saving rates of the elderly havebeen clearly lower than those of other younger households. Although the preconditionof the life cycle theory seemed to be met, the reality is more complex.
Dissaving is particularly evident in elderly households with no working family
members (Figure 2).9 Quantitatively speaking, the average household saving rate fell byaround 10 percentage points in the period between 1989 and 2009 (Table 2). The
contribution due to the declines in those of households with heads aged equal to or older
than 60 is estimated to be more than that, 11.2 percentage points. Although the life
cycle theory puts an emphasis on the effect of the age composition changes, they play aminor role of -1.2 percentage points or a tenth of the total decline.

7See Unayama (2010) for detailed examination of saving rate of various data sources.
Horioka (1991, 2004) argued that aging decrease aggregate household saving rate probably into a
negative territory due to retirements of baby boomers. However, Yashiro (2003) argued the effects ofretirement would be slow because baby boomers may prefer to continue working.
9Horioka (2010) examined saving rates of various household types and detected a large fall in elderly
household.
8-4-Figure 2 Gross Saving Rates by Age of Household Head

Table 2 Decompositions of variations of gross saving rate
Changes in official estimates
Changes in subsectoring
Contributions of changes in household compositions
Contributions of saving rate changesof whichhouseholdhead in early 40s
householdhead in late 40s
householdhead in early 50s
householdhead in late 50s
householdhead in early 60s
householdhead in late 60s
householdhead in 70s or older
Total contributions of household with head aged 60 or olderof whichcomposition changes
household without any worknig members
huosehold with working members

1989 to 2009 1989 to 1999 1999 to 2009 2004 to 2009
-10.8
-3.4
-7.4
-0.1
-9.7
-3.9
-5.8
-0.6
-1.9
0.1
-1.8
-1.2
-7.7
-3.9
-4.1
0.7
1
0.3
0.5
0.2
1
0.2
0.7
0.2
0.6
0.2
0.5
0.3
0.3
0.1
0.2
0-2.5
-1.9
-0.5
0.3
-3.3-1.4-2.1
0.1
-5.4
-1.8
-3.6-0.7
-11.2
-1.2
-5.9
-4.1

4. Implications for Redistribution Policies
A clear advantage of splitting household accounts is to make effects of redistribution
visible. Note that a major innovation of the 1993 SNA is to introduce a distinction
between primary and secondary income, thereby making income redistribution moreexplicit. However, without the breakdowns of the account, it is impossible to know whogets what. In other words, a full force of the innovation of 1993 SNA would be felt onlyif the breakdowns of household accounts are in place.
Figure 3(1) depicts the net receipts resulting from income redistribution accruing tohouseholds by heads’ age group in 2004 and 2009. The effect of income redistribution
should be measured by the difference between primary incomes and adjusted disposableincomes. Using (unadjusted) disposable incomes overlooks in-kind receipts, such as-5-healthcare and nursing care, thereby underestimating net receipts. Positive net receipts
are observed for households headed by those aged 65 or older in 2009, which isfinanced by the other household and bond issuance. Those in their early 60s weregainers in 2004, but turned into losers in 2009, mainly due to a gradual rise in eligible
age for pensioners.10
Now, we will proceed to further investigate the details of the changes between
2004 and 2009 (Figure 3(2)). An increase in the average figure may give a misleading
impression of reinforced income distribution functions. On the contrary, no age groupbut the late 50s gains in the period. Two age groups were hit hard—the early 40s andearly 60s. The increase in the average is brought about by compositional changes in thenumber of households. An increase in the number of elderly households produces
sufficiently large gains to totally offset negative effects due to changes in redistribution
policies. If the compositions had been the same, the average would have been minus¥100,000, not plus ¥50,000.
Figure 3 Net Receipts from Redistribution Policies(1) Net Receipt in 2004 and 2009(¥10,000)(2) Changes in Net Receipt between the Two Years(¥10,000)

5. Distributive Effects of Changes in Healthcare Systems
Figure 4 focuses on the distributive effects due to changes in healthcare systems
out of those in social security systems. On the benefit side, its ratio to disposable
income is around 3 percent in households headed by those in the early 50s or younger.
However, it is much higher for elderly households, especially 16 percent for those in10

To be specific, the eligible age was raised from 61 to 62 for males and 60 to 61 for females,
respectively.

-6-their 70s. On the contribution side, the ratio is approximately 5 percent, except for thosein the 60s or older age groups, whose ratio is smaller. As a result, positive net receipts
are gained only in households headed by those aged 60s or older.
Compared to the 2004, these results reveal larger net receipts in the 70s or older
group, while smaller in the 60s or younger group. Applying the 2004 systems to the2009 data gives us a clue to the difference. The differences mainly reflect changes indemographic and other socioeconomic factors outside the healthcare systems, except for
those in the 70s or older group, because the hypothetical exercise reproduces the results
close to the 2004 results.

Figure 4 Redistribution through Healthcare Systems

6. Conclusion
Sub-sectoring household accounts provides valuable information on aging. An increasein consumption by elderly households accounts for the increase in aggregate
consumption. This increase is attributed to not only an increase in number of suchhouseholds, but also their maintained consumption levels. The latter caused their saving
rates to plummet. A decline in aggregate saving rate mainly reflected that in elderly
households, which may fail the prediction of the life cycle theory that age compositional
effects matter.
Effects of redistribution were also masked by compositional effects, and therefore,
may misguide judgment in the period between 2004 and 2009. Although the net receipts
increased in 2009, compared to 2004, on average, most households suffered fromdecreased net receipts. The changes in healthcare systems themselves do not affect the-7-

overall picture significantly, and factors outside the system largely account for thechanges in net receipts.

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