Discussion Paper Series A

No.668

Getting Student Loans Right in Japan:
Problems and Possible Solutions

Lorraine Dearden(University College London and Institute for Fiscal Studies)
Nobuko Nagase(Ochanomizu University)

December2017

Institute of Economic Research
Hitotsubashi University
Kunitachi, Tokyo, 186-8603 Japan

Getting student loans right in Japan: problems and possible
solutions

Lorraine Dearden, University College London and Institute for Fiscal Studies
Nobuko Nagase, Ochanomizu University

Abstract
In this paper we take a detailed look at the Japanese university graduate labor market tounderstand more fully the problems with the current Japanese student loan system identified
in Kobayashi and Armstrong (2017). We see that unlike most other countries with a large
proportion of female university graduates, Japanese female graduates earn significantly lessthan male university graduates and this appears to be driven by significant wage falls whenfemale graduates marry or have their first child. This means that understanding the repayment
burden problems of the current student loan system and designing alternative income
contingent loan systems needs to take into account the household income of graduates. We
show that an affordable income contingent loan (ICL) system could be introduced in Japan,
however the repayments would probably have to be based on household income. We
illustrate this with a couple of example ICLs and highlight further work that needs to be done
to come up with a feasible and fair student loan system in Japan for post high school
education.

Acknowledgements
The authors are grateful for feedback received from Bruce Chapman and our discussantsNobuo Akai, Hideaki Tanaka, Hideo Akabayashi, Motohisa Kaneko and Naohiro Yashiro,
and other participants at the ‘Financing Higher Education in Japan’ conference held on 4 thOctober 2017 at International House, Tokyo. The authors are also grateful to Kazumasa Iwata
and Japan Center for Economic Research for their supports. Lorraine Dearden would like togratefully acknowledge financial assistance received from the ESRC funded Centre for theMicroeconomic Analysis of Public Policy at IFS (grant RES-544-28-5001) and the HEFCE
and ESRC funded, Centre for Global Higher Education at UCL – IOE (Grant no.
ES/M010082/1). Nobuko Nagase would like to gratefully acknowledge financial assistancereceived from the Japan Society for the Promotion of Science fund (KibanC15K03503), andalso by Joint Usage and Research Center Programs of Institute of Economic
Research, Hitotsubashi University. The use of Japanese Longitudinal Survey of Adults in the
21st Century (2002 Cohort) was allowed under the first competitive fund, and the use ofJapanese Labor Force Survey was allowed under these competitive funds to Nobuko Nagase.
The authors are grateful to the usage of JGSS as well. The Japanese General Social Surveys(JGSS) are designed and carried out by the JGSS Research Center at Osaka University of1

Commerce (Joint Usage / Research Center for Japanese General Social Surveys accredited by
Minister of Education, Culture, Sports, Science and Technology), in collaboration with theInstitute of Social Science at the University of Tokyo.

JEL Codes: H28, I22, I28, J24
Keywords: Student loans; student loan design; Japan.
Email: Lorraine Dearden: l.dearden@ucl.ac.uk;
Nobuko Nagase: nagase.nobuko@ocha.ac.jp

1.

Introduction

Kobayashi and Armstrong (2017) give an extensive overview of current problems with theJapanese Higher Education finance system as well as outlining recent reforms including therecent introduction of a small-scale income contingent style loan.
At the same time in Japan, there is evidence that the labor market for Japanese graduates ischanging. Increasingly, more university graduates are entering non-standard employment, or
employment with relatively low wages. Traditionally Japanese university students haverelied on parents to fund their university education but prolonged tight economic conditions
have impacted on the ability of parents to pay and in recent years the number of students
taking out JASSO student loans has been increasing rapidly. However, with increasing
numbers of graduates accessing non-standard employment and the longstanding low wages offemale graduates in the bottom half of the earnings distribution, this necessarily means thatan increasing number of graduates (and their families) are facing student loan repayment
hardship. There is also qualitative evidence suggesting that the cost of funding the educationof children is impacting on fertility decisions.
In this paper, we use Japanese micro data to look in detail at the problems identified by
Kobayashi and Armstrong (2017) with the current loan system and outline possible
approaches to solving these problems using a universally available income contingent loan
(ICL).
2

Our analysis shows that Japan is very different from other countries that have introduced
ICLs: simply borrowing an ICL scheme from these countries is unlikely to work. This ismainly because historically, female Japanese graduates have comparatively low earnings
compared to male graduates once they get married or have children. This is very different tocountries like Australia and the UK where the gender differences in the wages of graduates
are much less marked even after marriage or having a child. Whilst our analysis suggests that
this is changing for younger cohorts, Japanese cultural and economic factors mean this is
likely to be a feature of the graduate labor market for the foreseeable future. Hence asustainable ICL system will need to take this into account.
This also means that traditional RB analysis needs to be carefully interpreted in the Japanesecontext to get a full and nuanced picture of the current problems with the Japanese loansystem. It is also essential to keep in mind when considering ways to design a robust andaffordable student loan system going forward, including a universal and sustainable ICL
system advocated by Kobayashi and Armstrong (2017) and Armstrong, Chapman and
Dearden (2017).
In section 2 we look at recent trends in the Japanese graduate labor market and estimate age
earning profiles by percentile for Japanese graduates by gender as well as by marriage unit tohighlight the interesting features of the Japanese graduate labor market. In section 3 we show
the typical repayment burdens associated with the current JASSO loan system which clearly
illustrates why default rates have been increasing in Japan in recent times. In section 4 welook at the stylized implications of different types of ICL loan design for Japan and show
why a household based system is probably needed to ensure sustainability and fairness for theforeseeable future and in section 5 we conclude and highlight what further work needs to bedone to design an affordable and universally available ICL student loan system in Japan.

2.

The graduate labor market and graduate earnings in Japan

The percentage of high school graduates entering four year university (what we will term BA
graduates in this paper) has been rising steadily since the early 1990s as illustrated in Figure
1. Figure 1 shows that the percentage of high school graduates entering four year university is
on a rise, both for males and females. Females typically in the past went to two year junior3

college for post secondary education, but when the labor market for two year college
graduates stagnated, demand for two year college declined. Today, the proportion of women
undertaking four year BA degrees is at a historical high. Figure 1 also clearly illustrates thenarrowing of the gender gap in university enrolment over the period. This expansion has no
doubt been due to both the increase in provision of four year university facilities as well as
the expansion of loans available through JASSO to university students (see Kobayashi
Armstrong (2017)).
Figure 1: Four year BA degree enrolment by gender (percent)60
50

Percent

40
30
20
10
0
1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

Year
Females

Males

Source: Ministry of Education, Culture, Sports, Science and Technology Japan (MEXT)
School Basic Survey (Gakko Kihon Chosa)Figures 2 and 3 shows that males on average, have a higher probability of getting regularfull-time employment, seishain, once they have graduated from university or school. For
males, the ratio of seishain is around 50 percent for high school graduate one year after
graduation whilst for university graduates in 2002 and it was 69 percent and for graduates in2009 it was 74 percent. Further this proportion continues to rise every year after graduation
with around 90 percent of male university graduates in seishan jobs 10 years after graduation.

4

Figure 2: Percentage of Male Seishain by education group and years after graduation:
Graduates of 2002 and 2009
100%
90%
80%

70%
60%
50%
40%
30%
20%
10%
0%
1st Year2-3 years

4-5 years

6-7 years

8-9 years

10-11years 12-13 years

Years after graduation
12 years education, 2002 cohort

12 years education, 2009 cohort

14 years education, 2002 cohort

14 years education, 2009 cohort

16 years education, 2002 cohort

16 years education, 2009 cohort

Source: Source: Nagase (2017a) using Labor Force Survey (LFS) data.
On the other hand, from Figure 3 we seen that whilst female university graduates have ahigher percentage of seishain (70 percent) compared to female high school graduates (40percent), the percentage of seishain for all groups including university graduates declines
steadily every year after graduation. Whilst there has been an increase by around 5 to 7
percentage points in the proportion of seishain by age between the 2002 and 2009 cohort offemale university graduates, 12 years from graduation only 45 percent remain in seishain.
This reduction is generally associated with marriage and/or having a child (see Nagase(2017a) and Nagase(2018)).

5

Figure 3: Percentage of Female Seishain by education group and years after
graduation: Graduates of 2002 and 2009
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1st Year2-3 years

4-5 years

6-7 years

8-9 years

10-11years 12-13 years

Years after graduation
12 years education, 2002 cohort

12 years education, 2009 cohort

14 years education, 2002 cohort

14 years education, 2009 cohort

16 years education, 2002 cohort

16 years education, 2009 cohort

Source: Nagase (2017a) using Labor Force Survey (LFS) data.
For analyzing and designing student loan systems, it is important to see what implications
these labor market features have for the distribution of graduate earnings. To look at this we
use two Japanese data sources. The first is publicly available Japanese cross-sectional datafrom the Japanese General Social Surveys (JGSS). The second is Japanese Labor Force
Survey (LFS) data. JGSS surveys have been held in 2000, 2001, 2002, 2003, 2005, 2006,
2008, 2010 and 2012 and include data on education level, income and earnings of the main
respondent as well as household members including their spouse if married. We use datafrom all but the 2000 survey in our work to ensure sufficiently large graduate sample sizes.
Our LFS sample is taken from the monthly data of the 2015, 2016 and 2017 surveys. In both
samples, we restrict our sample to BA graduates or those with higher university qualifications
aged between 23 and 65. We also include in our sample individuals whose spouse has a BAor higher qualification (for our household analysis). Hence our two sources of income
estimate earnings profiles for graduates approximately 10 years apart on average. To
compare our two survey samples we put all earnings into 2016 prices using the Japanese
consumer price index (CPI).
6

If we limit ourselves to those main respondents in the JGSS who have BA degrees we have asample of 5243 individuals who approximately 2/3 are male (3,463). Most of our empiricalanalysis employs data from the repeated monthly cross-section of the Japanese Labor Force
Survey (LFS). This data was obtained from the Statistics Office for the period January 2015
to May 2017. The LFS is a nationally representative survey conducted every month thatcovers about 40,000 households and about 100,000 individuals over the age of 15. It is arotating panel and households are surveyed four times in the same months in two successive
years. From January 2002, the survey began to collect data on the fourth and last visit tohouseholds using a longer questionnaire which asked not only about labor force status, butalso about educational attainment, tenure, and annual income in the previous year for all
relevant individuals in the household. Data from this longer questionnaire is used in thisanalysis. We limit our sample to those who graduated from university or post-graduate study,
who are aged between 231 and 65 and who undertook their 4th interview in the LFS between
from January 2015 until May 2017. This leaves us with a sample of 53459 males (of whom5467 are post-graduates) and 29137 females (of whom 1656 are post-graduates).
As stated earlier, in designing student loan systems and for understanding the repayment
burdens associated with student loans it is important not only to know average graduate
earnings but graduate earnings across the entire earnings distribution. One problem with both
the JGSS and LFS earnings data is that it is banded into income groups rather recording theactual level. This makes estimating income profiles across the earnings distribution more
complicated. Following Dearden (2017) we get around this by using interval regression andthe rich covariates contained in the JGSS and LFS to estimate continuous earnings measures
within each income band.2
We then estimate calculate the raw percentile earnings by age and smooth these profiles using
flexible polynomials in age following Dearden (2017). The estimated earnings profiles for1

In both our JGSS samples and LFS samples we merge any 22 year old BA graduates with our 23 year old
graduates as the number of 22 year olds is relatively small.
2
The JGSS data has 20 income bands whereas the LFS data has only 10 income bands. Our explanatory
variables included tenure, hours of work, age, firms size dummy variables, marital status, dummy variables forage of children in households, number of children in the household, dummy variables identifying type of
employment, as well as detailed industry and occupation dummy variables. Full details are available from theauthors.

7

BA male graduates using both the JGSS and LFS data are shown in Figure 4 and thecorresponding estimates for females are shown in Figure 5.
From Figure 4 we see the estimated quantile earnings profiles are reassuringly similar when
we use the JGSS and LFS data. The only marked differences are for men on low income (the10th centile of the BA earnings distribution) where the LFS shows significantly lower
earnings. This simply could reflect the fact that the data is taken from different years (theLFS is a more contemporaneous cohort) or measurement error in one or both surveys or a
combination of both.3 There are also some differences at the 90th centile, but Dearden (2017)
showed that the interval regression method used for turning banded earnings into a
continuous measure is not as reliable for high incomes.
Figure 4: Quantile estimates of Male BA graduate earnings: LFS and JGSS data

1500

JGSS Data

0

0

500

1000

Annual Income ¥/10000 (2016 prices)
1000
1500
500

LFS Data

20 25 30 35 40 45 50 55 60 65
Age90th percentile
35th percentile

20 25 30 35 40 45 50 55 60 65
Age75th percentile
20th percentile

3

Median10th percentile

Male earnings in Japan have been declining since 1997, with some upturn after so called ‘Abenomics’ (theeconomic reforms of Prime Minister Abe) since 2013. The difference may reflect a real reduction in the bottom
10 percent of male earnings over this period. It could also reflect differences in response rates in the twosurveys. Response rates in the LFS are higher than those in the JGSS and this may mean coverage of lowearners Is better in the LFS.

8

In our analysis we concentrate on the LFS sample as it is more recent and involves larger
sample sizes. It suggests that median earning four year university educated males are earning
around 5 million yen by the age of 35 and this rises to about 7.5 million by the age of 55.
Males in the bottom 10th percentile never earn above 1.5 million yen per year. Those in the20th percentile of the earnings distribution earn about half of median earnings whereas thosein the 90th percentile earn between 50-75 per cent more than median earnings throughout
most of their working life. The variance in graduate earnings increases up until about the ageof 55 before narrowing in the run up to retirement. This is typical of most male earning
profiles seen in other countries and featured in this special issue of the EER.
In Figure 5 we see the corresponding estimates for females. This shows a very different
picture compared to males and compared to females in other countries. Typical age earning
profiles are only seen for women in the top quarter of the earnings distribution. Medianearning women never earn above 3 million yen per annum. It appears that the situation is
improving slightly for the slightly younger cohort covered in the LFS data4 but the increase inearnings is modest in all parts of the earnings distribution.

4

Nagase (2018) shows that the proportion of female university graduate continuing their seishain job after theirfirst childbirth has increased since 2013.

9

Figure 5: Quantile estimates of Female BA graduate earnings: LFS and JGSS data

800

JGSS Data

0

0

200

400

600

800
600
400
200

Annual Income ¥/10000 (2016 prices)

LFS Data

20 25 30 35 40 45 50 55 60 65
Age90th percentile
35th percentile

20 25 30 35 40 45 50 55 60 65
Age75th percentile
20th percentile

Median10th percentile

In Figures 6 to 8 we instead use LFS data look at household income of BA graduates where
we include the income of the BA graduates’ spouse if they are married. This is important
point to consider when we are considering the repayment burdens of the current JASSO
system or when designing a possible ICL systems as it is clear from Nagase (2017b) that
there are institutional reasons why a significant proportion of female BA graduates earn very
little. She shows that a significant portion of women quit work once they have a child, andfirm hiring policies often penalize workers who leave the labor market and re-enter during
middle age (predominantly mothers returning to work). A large proportion of firms pay
spouse allowance for long term employees who have dependent housewives, and thisallowance is often taken away when spousal earnings exceed tax threshold. This practice ischanging but has obvious disincentives for women working. In addition, the Japanese social
security system has protection for housewives who are exempted from social security tax but
are given rather generous coverage for basic pension, health and old age insurance so long as
their income is below 1.3 million yen a year. These tax and social security regimes coupledwith spouse allowance mean many married women earn just below these tax and social
10security thresholds. This bunching is very clear in the LFS data. There is currently a lot ofpolicy debate in this area in Japan, especially given demographic changes which has seen arapid decline in the working age population, but at the moment this is the context in which
student loans systems need to work.
To explore these issues more fully, we split our sample into 5 groups. Single male BA
graduates, single female BA graduates, Female BA graduates married to non-BA graduates,
Male BA graduates married to non-BA graduates and finally BA graduates who are married
to each other. We show the age earning profiles of these 5 groups by age of BA graduate.
With our final group we show the age earnings profiles based on the male BA graduate age
and the female BA graduate age. For our married profiles we start at age 25 due to therelatively low number of BA graduates married at ages 23 and 24.
Figure 6 shows the distribution of earnings by gender for single BA graduates by age fordifferent percentiles of the earnings distribution.

11

Figure 6: Quantile estimates of single BA graduate earnings: LFS data

1000

Females

0

0

200

400

600

800

Annual Income ¥/10000 (2016 prices)
1000
200
400
600
800

Males

20 25 30 35 40 45 50 55 60 65
Age90th percentile
35th percentile

20 25 30 35 40 45 50 55 60 65
Age75th percentile
20th percentile

Median10th percentile

Figure 6 shows that when we limit the sample to non-married males and females, the BA
gender wage gap narrows substantially and is the profiles and gender wage gap is similar to
the gender gaps seen in other countries. At the bottom of the income distribution there isvery little difference between men and women, and median earnings only significantly differ
from the age of 40. This could be a cohort rather than an age effect. It is only single BA
graduates in the bottom of the earnings distribution that will face potential hardship fromrepaying student loans. This is explored further in the next section.
Next we look at the household income of BA graduates who are married to non-BA graduatesby gender. This is shown in Figure 7.

12

Figure 7: Quantile estimates of household earnings of BA graduates married to non-BA
graduates: LFS data

1500

Females

0

0

500

1000

Annual Income ¥/10000 (2016 prices)
1000
1500
500

Males

25 30 35 40 45 50 55 60 65
Age90th percentile
35th percentile

25 30 35 40 45 50 55 60 65
Age75th percentile
20th percentile

Median10th percentile

We see that for this group, there are differences by gender, though not as marked as when we
only considered individual income of BA graduates. The profiles suggest that BA women
married to non-BA graduates whose household is below the 20th centile per cent of theearnings distribution will face financial hardship in repaying student loans and this will not benearly so severe for males married to non-BA females even in the 10th centile of thehousehold earnings distribution. Finally we look at BA male graduates married to BA female
graduates and this is shown in Figure 8. We see that the earnings profiles for this group,
whether we do it by male BA age or female BA age is significantly higher than for our othergroups and even couples in the 10th centile of the earnings distribution earn over 3 million
yen per year until their late 50s. Of course, these couples could have two loans which would
impact on the repayment burden but even this would only be problematic for a relatively
small minority of such couples.

13

Figure 8: Quantile estimates of household earnings of BA graduates married to BA
graduates: LFS data

2000

Females

0

0

500

1000

1500

Annual Income ¥/10000 (2016 prices)
1000
2000
1500
500

Males

25 30 35 40 45 50 55 60 65
Age90th percentile
35th percentile

3.

25 30 35 40 45 50 55 60 65
Age75th percentile
20th percentile

Median10th percentile

Repayment burdens for Japanese student loans

Currently BA students in Japan are able to take out Type 1 (based on merit and need) and/or aType 2 JASSO loan (based on need which has been gradually relaxed to include middle
income families) as is outlined in Kobayashi and Armstrong (2017). Type 1 loans are interest
free whilst Type 2 loans attract modest interest after university (currently 0.18 percent).
The repayment schedules for the different loans are shown in Table 2 of Kobayashi andArmstrong (2017) and the loan repayment length varies between 14 and 18 years for Type 1
loans and 13 to 20 for the more common Type 2 loans.
We concentrate on individuals or households in the bottom 20 th centile of the earnings
distribution and look at the repayment burdens associated with a Type 1 Jasso loan of 51,000
yen per month (the amount for an away from home individual at a national or local public
university) and a Type 2 Jasso loan of 80,000 yen per month (a relatively high Type 2 loan).
14

The repayment schedule for these two loans are given in Table 2 of Kobayashi andArmstrong (2017). The type 1 loans involves a monthly repayment of 13,600 per month over
15 years whereas the type 2 loan we are examining involves a monthly repayment of 16,270
yen per month over 20 years at current interest rates.5
The repayment burdens for individuals and by household type are shown in Table 1 for BA
males in the 20th centile of the earnings distribution and Table 2 for females in the 20th centileof the earnings distribution. We do not include married couples at ages 23 or 24 due to small
sample sizes. We can see from Table 1, that for males in the 20th centile of the various
earnings distributions, repayment burdens can be as high as 33.1 percent but are particularlyhigh for male graduates who are not married and hover at around 10 percent from the age of
27 for the larger loan and 8 percent for the lower loan having peaked at between 24 to 29
percent at age 23. At young ages, most men are not married, so this is a particular concern.
Table 1: Repayment burdens (%) for Males BA graduates in the bottom 20th percentileof earnings distribution by different household types

5

Age

All Males
own Income
onlyType 1 Type 2
Loan
Loan

23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41

27.7
13.8
9.9
8.1
7.1
6.5
6.1
5.9
5.7
5.5
5.4
5.3
5.1
5.0
4.9

33.1
16.5
11.8
9.7
8.5
7.8
7.3
7.0
6.8
6.6
6.4
6.3
6.1
6.0
5.8
5.7
5.5
5.3
5.1

HouseholdIncome notmarriedType 1 Type 2
Loan
Loan
24.2
14.5
11.1
9.6
8.7
8.3
8.1
8.0
8.0
8.0
8.2
8.3
8.4
8.5
8.6

28.9
17.3
13.3
11.5
10.5
9.9
9.6
9.5
9.5
9.6
9.8
9.9
10.0
10.2
10.3
10.4
10.4
10.5
10.5

Householdincome married to
non-BA graduate
Type 1 Type 2
Loan
Loan

7.7
6.2
5.4
4.9
4.6
4.4
4.3
4.2
4.1
4.0
4.0
3.9
3.8

9.2
7.4
6.4
5.9
5.5
5.3
5.1
5.0
4.9
4.8
4.7
4.7
4.6
4.5
4.3
4.2
4.1

Householdincome married to
BA graduate
Type 1 Type 2
Loan
Loan

4.7
4.1
3.7
3.5
3.4
3.3
3.2
3.2
3.2
3.1
3.1
3.1
3.0

Currently the interest rate on a Type 2 loan is 0.18% and the maximum that can be charged is 3%.

15

5.7
4.9
4.5
4.2
4.0
3.9
3.8
3.8
3.8
3.7
3.7
3.7
3.6
3.6
3.5
3.4
3.3

42

5.0

10.6

4.0

3.2

For women the problem seems much more extreme if we just base the RBs on a women’s
own income, but if we take into account the income of their spouse, women who are notmarried and in low earning jobs or those who marry non-BA spouses with low earnings faceparticular hardship. Again the majority of females are not married at young ages. This is nottrue for women who marry relatively low earning BA graduates, but the proportion of women
who fall into this group is relatively low for women aged in the early or mid 20s.
Table 2: Repayment burdens (%) for Females BA graduates in the bottom 20th
percentile of earnings distribution by different household types
Age

23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42

All Females
own Income
onlyType 1 Type 2
Loan
Loan
12.1
14.5
12.2
14.6
12.8
15.3
13.9
16.6
15.5
18.6
18.0
21.5
21.5
25.8
26.9
32.2
∞
∞
∞
∞
∞
∞
∞
∞
∞
∞
∞
∞
∞
∞
∞
∞
∞
∞
∞

HouseholdIncome notmarriedType 1 Type 2
Loan
Loan
15.8
18.9
12.2
14.6
10.5
12.6
9.6
11.5
9.2
10.9
8.9
10.7
8.8
10.6
8.8
10.6
8.9
10.7
9.0
10.8
9.2
11.0
9.3
11.1
9.4
11.3
9.5
11.4
9.5
11.4
11.4
11.4
11.4
11.3
11.3

Householdincome married to
non-BA graduate
Type 1 Type 2
Loan
Loan

8.1
7.9
7.7
7.6
7.5
7.4
7.4
7.4
7.4
7.5
7.6
7.8
8.0

9.7
9.4
9.2
9.1
8.9
8.9
8.8
8.8
8.9
9.0
9.1
9.3
9.5
9.8
10.1
10.5
11.0
11.5

Householdincome married to
BA graduate
Type 1 Type 2
Loan
Loan

4.4
3.8
3.5
3.3
3.2
3.1
3.1
3.1
3.1
3.1
3.1
3.0
3.0

5.3
4.5
4.1
3.9
3.8
3.8
3.7
3.7
3.7
3.7
3.7
3.6
3.6
3.5
3.4
3.3
3.2
3.1

In calculating there RBs, we have ignored the fact that JASSO loans since 2014 allow up to
10 year’s forgiveness in repaying a JASSO loan for those on low income (see Kobayashi and16Armstrong (2017)). This deferral, however, is not automatic and has quite low take-up
although the numbers seeking deferral has risen in recent years.
As mentioned earlier, graduates are single at the age of 23 and then either married or staysingle at a later age and we need to model this properly to understand fully the nature ofhousehold RBs across the life-cycle and across the earnings distribution. We simulate thesefamily formation transitions in next section in order to understand the fiscal implications of
ICL loan systems based on household income and compare this to systems based on
individual income.

4.

Possible directions for reform: universal income contingent loans

In this section we look an possible ICL loan designs for Japan. As outlined in Dearden(2017), in order to do this we need to simulate graduate earnings across the life cycle. Like
most other papers in this issue, we take a conservative approach and assume that graduates
stay in the same percentile of the earnings distribution over their entire life. As highlighted in
Dearden (2017), this will overestimate the cost of an ICL, particularly when there is highearnings mobility. Our simulations assume that 45% of graduates are females and 55% aremales.
Longitudinal data from the Japanese Longitudinal Survey of Adults in the 21st Century (2002
Cohort) suggests this is not the case for 4 year university graduates in Japan. The data is anational cohort covering men and women and their spouses who were aged between 20 and
34 years at the end of October 2002. We limit ourselves to BA graduates aged over 23 years
and pool together all transitions for this cohort. We divide earnings into quintiles by age andshow the resulting transition matrices for earnings at adjoining ages in Table 3.
It is clear from the table that there is a lot less income mobility in Japan than in the US (seeDearden (2017)) and Australia (see Higgins and Sinning (2013). This suggests that whilst we
will still over-estimate the costs of an ICL system, it will not be as much as with the estimatesin Barr et. al. (2017) using the same assumptions with US data.

17

Table 3: Earnings transitions for BA graduates in Japan at adjoining ages
Males

Females

Quintile of earnings distribution
at age t+1(percent)
1
2
3
4
5

Quintile of earnings distribution
at age t+1(percent)
1
2
3
4
5

1

74.99 19.20

4.15

0.96

0.70

89.18

1.66

0.54

0.89

2

12.17 60.35 23.40

3.30

0.77

11.43 58.53 22.30

6.23

1.50

3

2.72

15.79 58.18 19.46

3.85

4.95

11.06 63.61 18.15

2.22

4

1.3

2.87

18.40 55.99 21.43

3.33

3.39

11.37 68.28 13.63

5

0.80

0.90

3.2

2.67

1.88

3.48

Quintile ofearnings
distribution
at age t

12.93 82.17

7.74

14.66 77.31

For men there is very little earnings mobility and this is more prominent for high earning BA
graduates than low earning graduates. 82% of men in the top quintile of the earnings
distribution stay in the top earnings quintile in the following year. For females there is very
little mobility but this is strongest at the bottom of the earnings distribution. This reflects thefact that once women move out of the labor market, they are unlikely to return in thefollowing year.
As Kobayashi and Armstrong (2017) outline, Japan introduced an income contingent styleloan in 2017. This involved graduates paying back income at a repayment rate of 9% per yearof after tax income. There is basic deduction, employment income deduction and social
security contributions deductions that for example, for nominal 3 m yen, after tax income is1.19 m yen for single individuals. However, the scheme also involved a minimum repaymentof 2000 yen per month even when one has no afte tax income and a requirement for low
earning graduates who have persistent low incomes to repay their loan in full (after amaximum 10 years deferral).
We begin by considering an ICL which has a marginal repayment rate of 9% above nominal£3m yen but also has a lower marginal repayment rate of 5% for incomes between nominal
1.5m and 3m yen (as a substitute for the minimum repayment). This means that relatively low
earning graduates pay back part of their loan but ensures that the repayment burden remains
low. There is no requirement for low earning graduates to pay off their loan if there is
persistent low income. We begin by assuming:
18

•Debt of 244.8m yen (type 1 loan away from home)•

ICL with 5% marginal repayment rate above 1.5m yen and 9 % marginal repayment
rate above 3.0m yen.
•For example, after graduation, if a person earning 2.0 m yen per year would
pay, 5% of 0.5m i.e. 25000 yen per year. For the JASSO ICL, they require
payments of 24000 yen per year for all debtors with no taxable income, or
nominal income of below around 1.44m yen.

•

We compare the situation where the loan is written off after 25 years or where it isnever written off•

We have a zero real interest rate and assume a government discount rate of 0.18%.

•

The ICL is applied to individual BA graduate incomes and ignores the income of theirspouse.

The distributional implications of the loan by decile of lifetime earnings and gender is shownin Figure 9.

19

Figure 9: Distributional implications of ICL based on individual income: basline ICL
with 244.8m yen loan

80
60
40
0

20

0

20

40

60

Percent repaid

80

100

Females

100

Males

1 2 3 4 5 6 7 8 9 10 All

1 2 3 4 5 6 7 8 9 10 All

Decile of lifetime income

Decile of lifetime income

Write OffNo Write-off

With this ICL no graduate pays off their loan in full. This is because the real interest rate(0%) is below the government cost of borrowing (0.18%) so there is a small subsidy for all
graduates. Overall males pay between 80% (with loan write-off after 25 years) and 85% of
the loan (with no loan write-off). There is a very different story for women, with only those
women in the top 30% of the earnings distribution coming close to paying off the full valueof their loan. Overall, the ICL involves a subsidy of around 60% for women because of the
low wages they earn during their lifetime. This baseline ICL involves an overall subsidy of
38% with a write-off and 34% without a write-off. Whilst this will be an over-estimate
because of our no mobility assumption, it is clear that this scheme will involve a large
taxpayer subsidy.
What happens if we base it on household income instead? To do this, we simulate BA
household incomes over their lifetime. This involves simulating marriage dynamics andtaking into account the debt of the spouse when they enter the marriage (particularly
important for the case where two BA graduates marry. To do this we assume simulate20

earnings for 900 female graduates (45% of all graduates) and 1100 male graduates (55% of
all graduates) who will end up in 1,540 household units by the age of 40. Among thesehouseholds:•

We assumed 51% of female BA graduates and 42% of male graduates will end up
marrying each other (460 couples in our simulated sample)•

That 25% of male and 24% of female 4 year graduates will remain single•

That 32% of male and 25 % of female graduates will marry non-BA partners.

•

At the age of 23 virtually all graduates are single and these steadily change until theage of 40. We assume that households do not change after 40 (so we ignore divorce,
death etc).

For all BA graduates that stays single, we assume they stay in the same percentile of theearnings distribution throughout their life (like our individual analysis). We assume male
graduates who marry stay in same percentile of the appropriate married household income
distribution as they were in the single distribution. We assume that if they marry a BA female
graduate or non-graduate, her prior earnings percentile is unrelated to his (is random) but
remains fixed before her marriage. This is particularly important in order to simulate
outstanding debt for a BA graduate when two BA graduates marry. We assume all females
who marry get a husband whose earnings percentile is random and not related to their priorearnings.
How does this affect the estimated taxpayer subsidy for our baseline ICL? This is shown in
Figure 10. In this diagram, we compare the overall subsidy when based on individual income(average of the Male and Female results from Figure 9) with the subsidy based on basing the
ICL on household income.

21

Figure 10: Distributional implications of ICL based on individual versus householdincome: Baseline ICL with 244.8m yen loan

10 20 30 40 50 60 70 80 90

100

Household based ICL

00Percent repaid

10 20 30 40 50 60 70 80 90

100

Individual based ICL

1 2 3 4 5 6 7 8 9 10 All

1 2 3 4 5 6 7 8 9 10 All

Decile of lifetime income

Decile of lifetime income

Write OffNo Write-off

All of the analysis so far has been for relatively low debts and the ICL involves taxpayer
subsidies that are likely to be just under 20 percent. From Barr et. al. (2017) we see that there
are a number of ways to reduce the taxpayer subsidy of a loan. This includes increasing theinterest rate and/or applying a loan surcharge. As a final illustration we illustrate an ICL witha real interest rate and surcharge where:•

Every person who goes to university takes out a loan of 3m yen (average of JASSOType 1 Loan and Type 2 Loan during four years of university)•

Our ICL: 5% marginal repayment rate above 1.5m yen per year and 9% marginal
repayment rate above 3.0m yen per year•

We compare the situation where the loan is written off after 25 years or where it isnever written off

22•

A real interest rate of 0.18% is assumed. This is the same as the government assumed
government discount rate and applies whilst at university and at low earnings•

15% loan surcharge (i.e. 15% discount of the cost of loan if student doesn’t take outloan). For a loan of 3m yen, the outstanding debt to be repaid is 3mx1.15=3.45m yen.

In Figure 11 we compare this ICL when based on individual and household incomes.
Figure 11: Distributional implications of and ICL based on individual versus householdincome: ICL with interest rate and surcharge (3m yen loan)

80

100

120

Household based ICL

60
40
0

20

0

20

40

60

Percent repaid

80

100

120

Individual based ICL

1 2 3 4 5 6 7 8 9 10 All

1 2 3 4 5 6 7 8 9 10 All

Decile of lifetime income

Decile of lifetime income

Write OffNo Write-off

We see that the household based ICL collects between 81% (with 25 year write-off) and 90%(with no write-off) of the total value of the loans issued. This is likely to be an underestimate
because of assumption of no earnings mobility. The average value of the loan repaid varies
by household group measured at age 40 with the average being (for the case with no writeoff):•

101 percent for BA couples (despite having double the debt)•

103 percent for BA males married to non-BA females23•

94 percent for BA females married to non-BA males•

71percent for single males and•65 percent for single females.

This suggests that with a household based ICL those receiving the largest subsidies will besingle graduate households. These same individuals would receive an identical subsidy underan ICL which is individual based. Hence a household based ICL appears to be an effective
way of ensuring the university loans of women who marry rich partners are paid in full whilst
protecting households where overall income is relatively low.

5.

Conclusions

Kobayashi and Armstrong (2017) have highlighted the current problems with the Japanese
university student loan system. In this paper we have used a variety of Japanese micro data
sources to help understand the reasons behind the current problems.
One key issue identified is the unique nature of the Japanese labor market compared to othercountries and in particular the low earnings of female university graduates once they get
married and/or have a child. These low earnings appear in part to be driven by firm, tax andsocial security policy which gives generous tax breaks if wives earn no or low income. These
policies are currently under scrutiny and there is some evidence of changing behavior for
younger cohorts of women after marriage and having children, but it is likely to remain afeature of the Japanese graduate labor market for some time.
As Chapman (2017) makes clear, RB problems with most time based repayment student loansystems such as the current JASSO loans, can generally be solved in a fair and efficient way
by introducing income contingent student loans. However, the unusual features of theJapanese graduate labor market make a traditional ICL based on individual income hard todesign in a cost effective way and this means it is unlikely to be feasible or equitable in thecurrent Japanese climate.
We have shown, however, that a household based ICL system could work in Japan, thoughfurther work is needed to get more realistic simulations of both earnings and household
formation dynamics to better design the optimal ICL for Japan.

24

JASSO student loans are available to both two year college as well as four year university
students and future work needs to ensure that any ICL design would also work for two year
college graduates taking out loans. They have not been considered in our paper though it
would be relatively simple to include them in our simulations.
Incorporating realistic dynamics as well as two year college graduates will form the next partof our research so that we can devise a self-sustaining universal student loan system that is
equitable, affordable and ensures that all deserving students can take full advantage of posthigh school education in Japan without any financial barrier.

References
Armstrong, Shiro, Bruce Chapman and Lorraine Dearden (2017) Comments for JASSO on
the Planned Japanese ICL Reform. Personal correspondence to JASSO.
Barr, N. Chapman, B., Dearden, L. and Dynarski, S. (2017), ‘Getting Student Financing
Right in the USA: Lessons from Australia and the UK’, submitted to this EER issue.
Chapman, B. (2017), ‘Introduction to EER special issue’, submitted paper to this EER issue.
Dearden (2017), ‘Evaluation and designing student loan systems: an overview of empiricalapproaches’, submitted paper to this EER issue.
Higgins, T. and Sinning, M. (2013), ‘Modeling income dynamics for public policy design:
An application to income contingent student loans’, Economics of Education Review,
37: 273-285
Kobayashi and Armstrong, S. (2017), ‘Financing higher education in Japan and the need forreform’, submitted paper to this EER issue
Nagase, Nobuko (2017a) “2002-2015nen no josei shugyorituno henka: abenomikusu no koka
ha attaka? (Change in Labor Supply of Females during 2002-2015: Has Abenomics
Worked?) Tokei (Statistics) 68(2):54-58 (in Japanese).
Nagase, Nobuko (2017b), “Wage Gap between Long Term Employees and Hourly Workers:
the Effect of Bunching of Married Hourly Female Workers at Non-Tax Levied Income
Thresholds” Nihon Rodo Kenkyu Zasshi Special Issue (in Japanese), forthcoming
Nagase, Nobuko (2018), “Has Abe’s WOMANOMICS worked?” Asian Economic Policy
Review 13(1), forthcoming.
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