Economics of Education Review xxx (xxxx) xxx–xxx

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Economics of Education Review
journal homepage: www.elsevier.com/locate/econedurev

Student loans in Japan: Current problems and possible solutions
Shiro Armstronga, Lorraine Deardenb, , Masayuki Kobayashic, Nobuko Nagased⁎aAustralia–Japan Research Centre, The Australian National University, Australia
University College London, Institute for Fiscal Studies and IZA, United Kingdom
Center for Research and Development for Higher Education, The University of Tokyo, JapandOchanomizu University, Japanbc

ARTICLE INFOABSTRACT

Keywords:
Student loans
Student loan design
Japan

The Japanese higher education sector has seen increases in tuition with stagnant household incomes in a society
where family support for university students has been the norm. Student loans from the government have grown
rapidly to sustain the gradual increase in university enrolments. These time-based repayment loans (TBRLs) havecreated financial hardship for increasing numbers of loan recipients and their families. There is some evidence
that prospective students from low-income households are forgoing a university education to avoid student loan
debt. The Japanese government has introduced some measures including grants and a partial income-contingent
loan (ICL) scheme to help alleviate these problems.
While the ICL scheme is a positive development, this paper shows that it requires further refinement andbroader coverage if it is to adequately address the challenges facing higher education financing in Japan. We
show that an affordable and universal ICL system could be introduced in Japan that avoids problems with thecurrent partial income-contingent loan scheme and would help alleviate access issues for those from disadvantaged backgrounds. Importantly, the unique features of the Japanese labor market have to be carefully
considered, especially the large gender wage gap for married women. By introducing dynamics into modeling
graduate earnings and using carefully selected parameters, we show that it is possible to have a universal ICL
which achieves a balance between access and affordable repayment with minimal long-run costs to taxpayers.

JEL Codes:
H28
I22
I28
J24

1. Introduction
Japan's higher education sector is facing financing and accesschallenges. The country's aging population and low birth rates meanthat student cohort sizes are falling over time, while the number ofprivate universities continues to increase. The government's fiscal position, running primary deficits with a gross debt-to-GDP ratio of 245%
in 2018, makes subsidizing the sector increasingly difficult.
Furthermore, stagnant wages and household incomes, coupled with
gradually rising tuition fees, are making access to university a bigger
issue for society.
There are many challenges facing universities in Japan, such as theirdrive to internationalize and maintaining international competitiveness. For many private universities, financial viability is a growing
challenge and there are questions over quality in some private universities. Any reform or expansion of the student loan system would
need to involve provisions to ensure that loans are only available tohigh-quality universities for suitably qualified students. This is alreadyan issue with the current funding system.
At the same time, there is evidence that the labor market forJapanese graduates is changing as described in Section 3 below. Increasingly, more university graduates are entering non-standard employment with less job-security, so understanding the dynamics of thegraduate labor market is crucial to designing a sustainable loan system.
Traditionally, Japanese university students have relied on parents tofund their university education, but prolonged tight economic conditions have impacted the ability of parents to pay, and in recent years thenumber of students taking out student loans has increased rapidly. The
rising numbers of graduates accessing non-standard employment, andthe longstanding issue of low wages for female graduates in the bottom
half of the earnings distribution, have meant that an increasing numberof graduates (and their families) are facing student loan repayment
hardship. There is also qualitative evidence suggesting that the cost offunding the education of children is impacting on fertility decisions.1

Corresponding author.
E-mail address: l.dearden@ucl.ac.uk (L. Dearden).
1
According to the 15th Japanese Fertility Survey of 2015, 56.3% of couples replied that the cost of child-rearing and education was the reason for not being able tohave their ideal number of children. This reason was the highest of the 12 options given.
⁎

https://doi.org/10.1016/j.econedurev.2018.10.012
Received 29 October 2017; Received in revised form 24 September 2018; Accepted 28 October 20180272-7757/ © 2018 Published by Elsevier Ltd.

Please cite this article as: Shiro Armstrong, et al., Economics of Education Review, https://doi.org/10.1016/j.econedurev.2018.10.012

Economics of Education Review xxx (xxxx) xxx–xxx

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Fig. 1. Proportion of four-year BA degree enrolment by gender.
Source: MEXT, 2016b.

In this paper, we highlight the problems with the current Japanesehigher education loan system, including the recently introduced smallscale, partial-coverage, income-contingent loan (ICL) scheme. With an
ICL, graduates and other university leavers repay student loan debts
through employer with-holding once their incomes have reached acertain threshold, with no repayment until that threshold is reached.
We use Japanese microdata to look in detail at the current problems
with the Japanese student-loan system and outline possible approaches
to solving these problems using a universally available ICL.
Our analysis shows that Japan is different from other countries thathave introduced ICLs and that simply adopting an ICL scheme from anyof those countries is unlikely to work effectively. This is mainly because, historically, female Japanese graduates have comparatively low
earnings compared to male graduates once they get married or havechildren.2 This is very different from countries like Australia and theUK, where the gender differences in the wages of graduates are muchless marked, even after marriage or having a child.3 While recent evidence (Nagase, 2018a) suggests that this is changing for younger cohorts, Japanese cultural and economic factors mean it is likely to be afeature of the graduate labor market for the foreseeable future. Hence, asustainable ICL system would need to take this into account.
In Section 2, we provide a background to university funding andstudent loans in Japan. In Section 3, we look at recent trends in theJapanese graduate labor market and use data from the Japanese Labor
Force Survey (LFS) combined with panel data from the Japan Household Panel Survey (JHPS/KHPS)4 to simulate dynamic graduate earnings by gender. In Section 4, we show the typical repayment burdens
associated with the current Japanese mortgage-style loan system, whichhelps explain why default rates have been increasing in Japan. In
Section 5, we show why the current Japanese ICL scheme introduced in2017 does not solve this problem for low-earning graduates and how auniversal, affordable and sustainable ICL loan scheme could be introduced in Japan. Our work suggests that this would involve having
parameters that are different to the ICL schemes operating in Australia
and England but, we argue, would be significantly better than thecurrent mixture of TBRL and partial ICL loan arrangements. Section 6
provides a conclusion to the paper.
2. Policy background2.1. University enrolment and participation
As of 2015, there were 86 national universities, 89 public (or municipal) universities and 604 private universities and colleges competing for students in Japan (MEXT, 2016a).5 University enrolments
have been rising at an average rate of 1.4% per year over the last three
decades. This peaked at about 2.9 million students in 2011 and stood at
2.6 million in 2016 (MEXT, 2016a).
There are also other forms of tertiary education in Japan. The
number of students in specialized training colleges (senmongakko) has
increased considerably over the last four decades, from about 10,000 in
1977 to about 657,000 in 2016 whereas the number of students intechnical colleges (kotosenmongakko) has been stable since the mid1980s at around 60,000 students. Students in junior colleges peaked in
1995 at about 500,000, then fell to around 130,000 in 2016.6 Morestudents from lower income backgrounds attend specialized training
colleges than technical colleges or junior colleges. In this paper, we
focus on funding and loans for university students, but student loans arealso available to these other forms of tertiary education.
The percentage of high school graduates entering four-year university(what we will term BA graduates in this paper) has been rising steadily
for both males and females since the early 1990s, as illustrated in Fig. 1.
In the past, females typically went to two-year junior college for a postsecondary education. However, the demand declined when the labormarket for two-year college graduates stagnated and as the internal rateof return for four-year university programs surpassed that of two-year
junior colleges for women. Today, the proportion of women undertaking
four-year BA degrees is at a historical high at just under 50%.
Fig. 1 also illustrates the narrowing of the gender gap in university
enrolment since the early 1990s. In 2016, 44.1% of university students
were women—more than double the number than in 1992.7 This increase
has no doubt been due to the growing demand for higher education, as
well as to the increase in the provision of four-year university facilities andthe expansion of loans available to university students through the Japan
Student Services Organization (JASSO). JASSO is a quasi-governmental
agency and is the largest provider of student loans in Japan.

2

In this paper, we use wages in an hourly context, and earnings to account forannual income from work excluding non-salary components.
3
Japan had the third largest gender wage gap in the OECD in 2017, significantly higher than that of Australia or the United Kingdom, source: http://
www.oecd.org/gender/data/gender-wage-gap.htm
4
We use the combined Japan Household Panel (JHPS/KHPS) survey, whichmerges data from the “Keio Household Panel Survey” (KHPS) from 2004 withdata from the “Japan Household Panel Survey” (JHPS), which started in 2009.
See https://www.pdrc.keio.ac.jp/en/paneldata/datasets/jhpskhps/ for more
information about the panel data.

5

Ministry of Education, Culture, Sports, Science and Technology (MEXT).
See MEXT (2016a).
7
See MEXT (2016a).
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Fig. 2. Tuition fees 1955–2014.
Source: MEXT, Changes in Tuition Fees of National Universities and Private Universities (http://www.mext.go.jp/b_menu/shingi/kokuritu/005/gijiroku/attach/
1386502.htm).

Fig. 3. The ratio of tuition fees to family disposable income.
Note: the ratio is tuition fees for one year to monthly family disposable income.
Source: MEXT (see Fig. 2 source note) and Statistical Bureau “Household Survey”.

2.2. University tuition fees

funding, and the trend of reduced subsidies is likely to continue.
Government subsidies to private universities and colleges were stable
over that 12-year period, although the ratio of subsidies to current
expenditure decreased to less than 10%. Almost three out of four students attend private universities in Japan.
Although the increase in tuition fees has been modest in recent
years, family disposable income has been decreasing. This has led to a
gradual increase in the ratio of tuition fees to family disposable income(Fig. 3). In Japan and other East Asian countries, parents have traditionally been responsible for financing the education of their children.
Thus the burden of tuition on families has been increasing, especiallyfor low-income families.
The household share of higher education expenditure is more thanhalf of the total expenditure on higher education in Japan, and among
the most expensive in the world (see OECD, 2015). Public expenditureon tertiary education is among the lowest for OECD countries. Households in Japan already bear a significant burden of higher education
costs, but the cost-sharing trend in Japan, as elsewhere, is moving awayfrom public toward private sources.
While tuition fees of Japanese universities and colleges have become less affordable, the availability of public grants and scholarships

University tuition fees for both national and private universities rose
dramatically between the late 1970s and early 2000s. Since then, national university tuition fees have plateaued, and those for private
universities have grown much more slowly (Fig. 2). The slowdown in
the growth of tuition coincides with the stagnation of wage growth andthe onset of deflation in the late 1990s following the slowdown of theJapanese economy after the asset bubble burst at the beginning of that
decade. The tuition fees charged by national universities in 2016 weremore than 40 times higher than in 1972 in current prices.8 The increasein expenditure and limited capacity for government subsidization has
led most universities and colleges to raise their fees.
Government subsidies to national universities have been falling by
1% per year since 2004. Government spending was about 12.4 billion
yen in 2004 and declined to about 10.9 billion yen in 2016. Given theJapanese government's fiscal position, there is little capacity for further
8
All values are reported in current prices unless otherwise specified. The CPI
was at or slightly below zero since the late 1990s until the mid-2010s.

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Fig. 4. Changes in student numbers receiving JASSO loans.
Source: Nihon Ikueikai (Japan Student Scholarship Foundation) and JASSO Annual Reports, various years.

for undergraduate students both in the public sector and the private
sector has decreased. The exception is with university tuition waivers
which are equivalent to student grants. The budget for tuition waivers
for students increased from 21.5 billion yen in 2004 to 43.4 billion yen
in 2017 (MEXT, 2017). Each university has discretionary power todecide how to allocate tuition waivers.

Students apply for the loans and are selected through the school fromwhich they graduate prior to university or through the Higher Education
Institutes (HEIs) they attend. Students taking on a JASSO loan must havea parent and other relative agree to act as a guarantor on the loan, or
have the Japan Educational Exchanges and Services (JEES) act as an
institutional guarantor. Overdue repayments are charged interest at therate of 5% per year. This rate is significantly lower than the 10% per year
charged until the end of March 2014. If the loan recipient is unable torepay the loan, legal action is taken against the guarantor. In the case of
the institutional guarantor, JEES is likely to take legal action against theloan recipient if they are unable to repay. There are provisions for deferment and reduced repayments if facing hardship, but individuals haveto apply for this annually. 30% of Type 1 students who undertake
graduate degrees can have their loans partially or wholly exempted ifthey have an “outstanding” academic record. Both Type 1 and Type 2
borrowers account for just under 40% of all university students andaround 45% of all students. The rate of collection, as reported by theadministering agency JASSO, was 96.7% in the fiscal year 2015.10
When modeling student loan design, it is important to know the
distribution of loan amounts and who takes out loans. The distributionof loans for four-year university students excluding night students froma 2014 JASSO sample survey (with population weights) is shown in
Table 1. We use the more disaggregated version of this data in our simulations below. The average monthly loan was 75,724 yen.

2.3. Student loans
The growth in university enrolments has been sustained by an increase in student loans provided by the government and, in particular,
student loans from JASSO. JASSO provides two types of time-based
repayment loans (TBRLs), which require repayment at fixed time intervals. Of the two types of loans, the growth of Type 1 (interest-free)loans has been modest (Fig. 4), while the growth of Type 2 (low-interest) loans, introduced in 1984, has been increasing rapidly, both for
four-year and two-year undergraduate students. The dramatic growthof Type 2 loans is due to the substantial relaxation of eligibility criteria
in 1999.
Type 1 loans are awarded based on both merit and need. They areinterest-free and not indexed to inflation. Type 2 loans are interest-freeduring university years, with a maximum interest rate of 3% after
graduation, and are awarded based on economic need, though theeligibility criteria are widening to include those from middle-income
families. The interest rate charged on Type 2 loans is negligible at
0.33% for the fixed interest rate option and 0.01% for the variable interest rate that is altered every 5 years (as of May 2017—see
JASSO, 2017). Neither loan type is associated with fees.
The total budget for both types of loans was 1.08 trillion yen in thefiscal year 2017, having fallen from a peak of 1.2 trillion yen in thefiscal year 2013.9
The size of each loan varies according to the type of loan, whether
the student is attending a private or national/public university, andwhether they live at or away from home. Loan amounts for Type 1 loans
vary from 45,000 yen per month for four-year university students living
at home attending a national or public university, to 64,000 yen permonth for four-year university students attending a private university
away from home. The time-based repayments require monthly instalments for periods of 13–20 years depending on the loan amount (seeJASSO, 2017).

2.4. Recent reforms to Type 1 loans
A new ICL scheme was adopted in April 2017 for Type 1 JASSO loanborrowers. Type 1 JASSO loans covered around 37% of borrowers and
14% of university students in 2016 (Fig. 4). The ICL option is notavailable for those borrowers taking out the more common Type 2 lowinterest student loans as of 2017. Repayment rates are contingent on
income under the new scheme. The repayment rate is 9% of the borrower's taxable income. A borrower can choose between a TBRL with
fixed monthly repayments or the new ICL plan before graduation.11
Taxable income in Japan is gross income minus income deductions forearned income deduction, social security contributions (pension andhealth insurance), basic personal deduction and spouse deduction(contingent on both the primary earner's and spouse's gross earnings).
10

See JASSO (2017), p. 7.
Borrowers can change from TBRL to ICL after graduation once, but not theother way around.
11

9

JASSO (2017), p. 6.
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For males, the ratio of seishain is around 50% for high school graduates
one year after graduation, while for university graduates in 2002 it was
69% and for graduates in 2009 it was 74%. This proportion continues torise every year after graduation, with around 90% of male university
graduates in seishain 10 years after graduation (Nagase, 2017).
While female university graduates have a higher percentage ofseishain (70%) compared to female high school graduates (40%), thepercentage of seishain for both groups declines steadily every year after
graduation. While there has been an increase of around 5–7 percentage
points in the proportion of seishain by age between the 2002 and 2009
cohorts of female university graduates, only 45% remain in seishain 12
years after graduating. This reduction is generally associated withmarriage and/or having a child where more women leave the labor
force or change their jobs to non-standard employment. Mothers often
re-enter the labor market, but mostly as non-standard hourly employees, instead of as seishain. There has been some increase in university-graduated mothers continuing to work as a seishain after the
short hour option was mandated in 2010, and also as a result of the
combination of Womanomics policies after 2013 (Nagase, 2018a).
Seishain, or standard employment, is associated with higher incomesthan non-standard employment and the share of women in seishain
work falling with age is causing a persistent and widening gender wage
gap.

Table 1
Distribution of JASSO loans in 2014.
Source: JASSO Students’ Survey (2014) – calculated from microdata of JASSO“Student Survey 2014″ for four-year university students, excluding night students.
JASSO monthly loan
in yenNumber of
students

Distribution
among allborrowers (%)

Distribution
among all students(%)

5–30,000
30,001–40,000
40,001–50,000
50,001–60,000
60,001–70,000
70,001–80,000
80,001–100,000
100,001–125,000
125,001–150,000
150,001–270,000
No loanAll students

98,977
101,886
24,963272,996
129,764
67,495
148,731
105,031
71,40346,713
1,318,644
2,386,600

9
10
2
26
12
6
14
10
7
4

4
4
1
11
5
3
6
4
3
2
55
100

The scheme involves a minimum repayment of 2,000 yen per monthfor borrowers with gross annual incomes of between zero and 1.44
million yen a year (equivalent to a taxable income of between 0 and
0.27 million yen).12 The 2,000 yen per month minimum repayment is
an attempt to balance the interest of recovering ICL debts in an environment with high government debt and fiscal pressure. If a low
earning graduate has a high earning partner then they are put back on
the TBRL rather than the ICL. As is the case in Australia, the debt iswritten off only if the borrower becomes disabled, permanently ill, or in
the event of death.

3.2. The distribution and dynamics of graduate earnings in JapanFor analyzing and designing student loan systems, it is important to
see what implications these labor market features have for the distribution of graduate earnings by age, as well as earning dynamics forJapanese graduates. To look at this, we use two Japanese data sources.
The first is the Japanese LFS data, which is the best source of crosssectional earnings data in Japan. Our LFS sample is taken from themonthly data of the 2015, 2016, and 2017 surveys. Our second sourceof data is the combined Japanese Household Panel Survey (JHPS/
KHPS) which covers the period from 2004 until 2016.
The LFS is a nationally representative survey conducted every
month that covers about 40,000 households and about 100,000 individuals over the age of 15. It is a rotating panel and households are
surveyed four times in the same adjacent two months in two successive
years. From January 2002, the survey began to collect data on the
fourth and last visit to households using a longer questionnaire, which
asked not only about labor force status, but also about educational attainment, tenure and annual income in the previous year for all relevant
individuals in the household. Data from this longer questionnaire areused in this analysis. We limit our sample to those who graduated fromuniversity or postgraduate study, aged between 2313 and 65, and who
undertook their fourth LFS interview between January 2015 and May
2017, giving a sample of 53,459 males and 29,137 females.
Our JHPS/KHPS panel consists of 4,950 university graduates followed for between 1 and 13 years, with the average time in the panel
being 8.13 years. 64.4% of the panel are males and 35.6% females. For
those aged 23 in our panel, 57.1% are males and 42.9% females, reflecting the increase in university participation by women illustrated inFig. 1. This means we have 28,496 graduate earnings observations:
18,309 for males and 10,187 for females.
In designing student loan systems and 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 the LFS earnings data is that it
is banded into income groups rather than recording the actual level
which makes estimating income profiles across the earnings distribution more complicated. Following Dearden (2018), we get around this

3. The graduate labor market and graduate earnings in Japan
3.1. The Japanese graduate labor market
Up until the late 1980s, the graduate labor market in Japan wasquite stable and most graduates found long-term employment after
graduation. After the asset bubble burst in 1991, the conditions in thegraduate labor market worsened as the economy stagnated. The
Japanese economy has experienced slow growth since then, withgrowth averaging below 1%. One feature of the Japanese labor market
is the "lifetime employment" system (seishain) where once a graduate
gets a full-time job in a company or civil service at graduation, he or she
is entitled to work there until the mandatory retirement age. The system
also includes seniority-based wages where earnings increase with tenure. The seishain system guarantees stable employment and was apositive feature of the labor market during periods of rapid economic
growth because firms could invest heavily in the human capital of
employees without fear of losing them to competing firms. With astagnant economy, some argue that the system is now a drag on theeconomy given that it inhibits labor mobility (Yashiro, 2011).
Labor market flexibility has been introduced with an increase in theshare of non-regular employment (non-seishain) that does not featurelong contracts, significant job security or seniority pay. This has led to abifurcation of the labor market (Miyamoto, 2016) with roughly 40%
now nonregular workers. This has meant that graduates who do notfind stable or full-time employment may have difficulty with loan repayments between jobs.
Data from the Japanese Labor Force Survey (LFS) show that males
on average have a higher probability of getting regular full-time employment, seishain, once they have graduated from university or school.
12
See JASSO (2017) and Fig. 11 below. Annual revenue is what we refer to as
gross earnings. Total income is what we refer to as taxable income. The JASSOICL is 9% of taxable (total) income.

13
In our LFS sample we merge any 22-year-old BA graduates with the 23year-old graduates, as the number of 22-year olds is relatively small.

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by using interval regression and the rich covariates contained in the LFS
to estimate continuous earnings measures within each income band.14
This is not necessary for the JHPS/KHPS panel data where earnings are
not banded.
We then calculate the percentiles of the earnings distribution (including zeros) in both data sets and smooth these profiles using flexible
polynomials in age following Dearden (2018). The estimated ageearnings profiles for BA male graduates using both the LFS data and
JHPS/KHPS panel data are shown in Fig. 5 and the corresponding estimates for females are shown in Fig. 6.
From Fig. 5 we see that for males, the estimated quantile earnings
profiles are reassuringly similar when we use the JHPS/KHPS panel
data and LFS data. The only marked differences are for men with relatively high earnings (the 75th percentile and 90th percentile of the BA
earnings distribution). The LFS shows lower earnings at the 75th percentile and higher earnings at the 90th percentile from the age of 40
onwards. This simply could reflect the fact that the data is taken fromdifferent years (the LFS is a more contemporaneous cohort whereas the
JHPS/KHPS covers the years 2004–2016) or the censoring of the LFS athigh earnings. There is also an issue of higher attrition in the panel for
those in the lowest and highest income groups.15 Dearden (2018)
showed that the interval regression method used for turning banded
earnings into a continuous measure is not as reliable for high earnings,
and this may explain some of the observed differences.
In our analysis, we use percentile estimates from the LFS sample as
it is more recent and involves larger sample sizes. The data suggest thatmedian-earning, four-year university-educated males are earning
around 5 million yen by the age of 35. 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 the 20th percentile of the earnings distribution earn about half of the median earnings whereas those in the90th percentile earn between 50–75% more than median earnings
throughout most of their working life. The variance in graduate earnings increases up until about the age of 55 before narrowing in the runup to retirement. This is typical of most male earning profiles seen inother countries and featured in this special issue of the EER.
In Fig. 6, we see the corresponding estimates for females. This showsa very different picture compared to males and compared to females inother countries. Typical age-earnings profiles are only seen for womenin the top quarter of the earnings distribution. Median-earning women
never earn above 3 million yen per annum, and at most ages earn well
below this figure. It appears that the situation is improving slightly forthe younger cohort covered in the LFS data,16 but the increase inearnings is modest in all parts of the earnings distribution. There are,however, significant differences in the earning profiles from the twodata sets, particularly at older ages. This may be due to cohort effects.

Dearden and Nagase (2017) compared the same LFS data with datafrom the cross-sectional Japanese General Social Surveys (JGSS) between 2000 and 2012. Both data sources gave very similar profiles atyounger ages, with small differences emerging at older ages likely due
to cohort effects (lower earnings in the JGSS data at older ages). Thissuggests the observed differences between our panel data and LFS isprobably due in part to cohort effects, but also to panel attrition, nonresponse issues and/or relatively small sample sizes.17
What lies behind the low female earnings? What is clear from the
LFS data is that it is not low labor force participation. It is instead low
earnings for graduate women in work. Interestingly, at young ages,
women in the bottom half of the graduate earnings distribution earnmore than males in the bottom half of the earnings distribution. This isbecause young male graduates remain unemployed in order to obtainseishain while female graduates are more likely to opt for some earnings
in non-seishain (Nagase, 2011).
Nagase (2018b) argues that there are further institutional reasons
why a significant proportion of female BA graduates earn very little.
She shows that a significant portion of women quit full-time work, or
any paid work, once they have a child, and firm 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 a spouse allowance for long-term employees who
have dependent housewives, and this allowance is often taken awaywhen their spouse's earnings exceed the first tax threshold or social
security tax exemption, though the policy differs according to firms.
This practice is changing, but still has obvious disincentives for
women working. In addition, the Japanese social security system has
generous protection for the spouses of wage earners. They are exemptedfrom social security tax and given rather generous coverage for basic
pension, as well as full coverage of health and old age insurance, so longas their earnings are below 1.3 million yen a year. From September
2016, part-time workers earning more than 1.06 million yen a year andworking 20 hours or more a week at firms with over 500 workers arelevied social security tax. These tax and social security regimes coupledwith spousal allowance and deductions mean many married womenearn just below these tax and social security thresholds.18 Thisbunching is very clear in the Ministry of Health, Labor and Welfare's
Longitudinal Survey of Adults in the 21st Century data as shown by
Nagase (2018b). There is currently a lot of policy debate in this area inJapan, promoted in part by significant demographic changes whichhave seen a rapid decline in the working age population; this is thecontext in which the student loans system needs to work.
If we instead focus on the earnings of single BA graduates, the genderdifferences are much less stark as shown in Fig. 7. It shows that when
we limit the sample to non-married males and females, the BA genderwage gap narrows substantially, and 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 again could be a cohort
rather than an age effect. Of single BA graduates, it is only those in thebottom of the earnings distribution that will face potential hardshipfrom repaying student loans. This is explored further in Section 4.

14
The LFS data has 10 income bands. Our explanatory variables include:
tenure, hours of work, age, firms size dummy variables, marital status, dummy
variables for ages of children in households, number of children in the household, dummy variables identifying the type of employment, as well as detailed
industry and occupation dummy variables. Full details are available from theauthors.
15
Male earnings in Japan have been declining since 1997, with some upturn
following the so-called ‘Abenomics’ policies (the economic reforms of Prime
Minister Shinzo Abe) since 2013. The difference may reflect some real differences in earnings because of the different time periods covered; it could also
reflect differences in response rates in the two surveys. Response rates in the
LFS are significantly higher than those in the JHPS/KHPS, and panel attrition
will make this problem worse as the panel ages (Naoi & Yamamoto, 2010). This
almost certainly means that coverage of low earners will be better and more
representative in the LFS. Differences at high earnings are not particularly
crucial for loan design unless there is very high earnings mobility. This is not
the case in Japan.
16
Nagase (2018a) shows that the proportion of female university graduates
continuing their seishain job after the birth of their first child has increased since2010, and it further increased after 2013.

3.3. Introducing earning dynamics
We follow the method of Dearden (2018) and use our age-earnings
profiles by percentile from the LFS survey to approximate the marginal17

See Naoi and Yamamoto (2010) for more details.
From 1.03 million yen a year, tax is levied for wage earners. From 1.3
million yen a year, a spouse would need to pay their own social security tax.
The threshold for claiming spousal deduction has been raised from 1.03 million
to 1.5 million per year from 2018. All these changes are included in our simulations below.
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6Economics of Education Review xxx (xxxx) xxx–xxx

1000

1500

JHPS/KHPS Panel Data

144 300 500

Annual earnings (10,000 yen, 2016 prices)

1000

1500

LFS Data

144 300 500

Annual earnings (10,000 yen, 2016 prices)

S. Armstrong, et al.

20 25 30 35 40 45 50 55 60 65
Age

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

75th percentile
20th percentile

Median10th percentile

Fig. 5. Quantile estimates of male BA graduate earnings: LFS and JHPS/KHPS data.

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

800
600
144 225 300 400

600Annual earnings (10,000 yen, 2016 prices)

800

JHPS/KHPS Panel Data

144 225 300 400

Annual earnings (10,000 yen, 2016 prices)

LFS Data

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

Median10th percentile

Fig. 6. Quantile estimates of female BA graduate earnings: LFS and JGSS/KHPS data.

distribution of graduate earnings at each age from 23 to 65, which wewill use in our simulations.
We then use copula models to estimate the joint distribution of theadjoining continuous marginal cumulative distribution function (CDF) of
earnings at each age in our JHPS/KHPS panel data.19 From Sklar (1959)
we know there exists a copula function that exactly defines this joint
bivariate distribution. In Japan, we have up to 13 earnings observations
per individual, but we find that a bivariate copula, which assumes firstorder Markov dependence, matches the dependence observed in thepanel data well. Our estimation approach involves finding the bivariate
copula that best captures the joint distribution of the adjacent marginal
earnings distributions, essentially the continuous transition matrix for
earning rank transition from the age of 23 to 64 and hence similar to thetransition matrix approach of Higgins and Sinning (2013).
As was the case for the US (see Dearden, 2018,), Brazil (Dearden &Nascimento, 2018) and England (see Dearden, Fitzsimons, Goodman, &Kaplan, 2008), the t-copula provided the best fit for most age transitions for both male and female graduates in the JHPS/KHSP panel. As
explained in Dearden (2018), the t-copula has two parameters: thecorrelation parameter ρ (rho) and the degrees of freedom parameter ν(df). The ρ parameter describes the overall level of immobility inearning transitions, with a higher ρ meaning less earnings mobility
between adjacent ages. The ν parameter measures the extent of taildependence in the transition. The lower the ν parameter, the lower themobility in the tails of the earnings distribution. Figure 8 shows theresults of our estimation procedure (and confidence interval for theestimates), as well as non-parametrically, smoothed estimates of rho,
which we use in our simulations.20
The estimates of rho in Fig. 8 show an increasing level of immobility
in the earnings distribution for graduates in Japan until late their 50s
for both men and women, with slightly more immobility for women.
Earnings become significantly more mobile for males after that time

19
The marginal CDFs are uniformly distributed between 0 and 1 and hence
can be easily mapped onto the percentile estimates of the marginal distributions
at each age once the simulations have been completed.

20
We smooth estimates up to the age of 59. It is clear that in our data, many
graduates retire at the age of 60. For these transitions, we use our raw (unsmoothed) estimates.

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Economics of Education Review xxx (xxxx) xxx–xxx

200

400

600

800

1000

Females

0

200

400

600

800

Annual earnings (10,000 yen, 2016 prices)

1000

Males

0

Annual earnings (10,000 yen, 2016 prices)

S. Armstrong, et al.

20 25 30 35 40 45 50 55 60 65
Age

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

75th percentile
20th percentile

Median10th percentile

Fig. 7. Quantile estimates of single BA graduate earnings: LFS data.

.9
.6

.7

.8

Rho

.8
.6

.7

Rho

.9

1

Females

1

Males

20 25 30 35 40 45 50 55 60 65
Age

20 25 30 35 40 45 50 55 60 65
Age

Estimated rhoCI

Rho used in simulations

Fig. 8. Estimates of rho (ρ) from t-copula.

(particularly around the age of 60) and slightly more mobile for females(with less of a decline at 60). Fig. 8 implies considerably less earnings
mobility among graduates in Japan compared to US graduates examined by Dearden (2018) and Brazilian graduates examined in
Dearden and Nascimento (2018).
The other parameter, ν (the degrees of freedom), measures tail-dependence; that is, excess immobility in the tails of the distribution. The
lower the ν parameter, the lower the mobility in the tails. Fig. 9 showsby age the degrees of freedom estimates (df or v), the confidence intervals, and the corresponding non-parametrically smoothed estimatesof v for both males and females.
Fig. 9 shows that individuals at the bottom (or top) of the earnings
distribution face higher chances of upward (or downward) mobility inthe first years after graduation but not after. However, because there
are large confidence intervals at early ages some caution is needed withthis conclusion. We also repeat this exercise and estimate household
earning dynamics for BA graduates, which allows us to simulate theearnings of the partners of BA spouses (crucial in calculating taxable
income, which is the basis of the current JASSO ICL loan). This is discussed in Section 5.
Having obtained our t-copula estimates, we have a relatively
straightforward way of simulating forward for a sample of 23-year-old
graduates. We assume that 45% of graduates are female and 55% aremales.21 Our simulation approach involves:

21
Recall that in 2016, 44.1% of four-year university graduates were females(see MEXT, 2016a), so 45% seems like a reasonable assumption for a cohort
starting university now.

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Degrees of freedom
4
6
0

2

4
0

2

Degrees of freedom

68Females

8Males

20 25 30 35 40 45 50 55 60 65
Age

20 25 30 35 40 45 50 55 60 65
Age

Estimated dfCI

df used in simulations

Fig. 9. Estimates of degrees of freedom (ν) from t-copula.

Of course, mobility and dependence trends are likely to change for
future graduates and, as mentioned earlier, there is growing evidence ofincreasing mobility in Japan as the graduate labor market changes. The
copula models used in this paper only consider first-order rank dependence, and it appears that this might not be totally adequate (asevidenced by the slightly lower correlation for earnings 3 years apart).
If we have too much mobility in our simulations, we will underestimate
the cost of an ICL loan system (Dearden, 2018). Table 2, however,suggests that this is unlikely to be very large.

Table 2Comparison of earnings correlations in JHPS/KHPS panel data and simulated
earnings data.
Lag

Males
JHPS/KHPS Panel

Simulations

Females
JHPS/KHPS Panel

Simulations

1
2
3

0.88560.82410.76830.90670.82480.74870.8821
0.8324
0.79630.91590.83890.7677

1 Drawing a sample of 9,000 females and 11,000 males aged 23 whoare placed in 100 percentiles of the earnings distribution (90 womenand 110 males in each percentile).
2 Estimating the conditional distribution of the marginal CDF at age
24 (u24) given the marginal CDF at age 23 (u23) which is given by:
cu23 (u24) = u C23 (u23, u24)
23
where C23 is the t-copula with parameters v and ρ from oursmoothed estimates at age 23.
3 Generating a random standard uniform variable r with the same
dimension as u23 (9,000 for females and 11,000 for males).
4 Generating u24 = cu231 (r ) to get our uniformly distributed predicted
rank at age 24, which has a stochastic element due to the rank
prediction being partly determined by the draw from the random
uniform.
5 Repeat steps 2 to 4 for each sequential age. This gives us the predicted percentile of every individual at each age from 23 to 65.
6 Matching in smoothed percentile earnings estimates by age andgender from the LFS (some of which are shown in Figs. 7 and 8) toobtain our lifetime earnings simulations.

4. The need for reform of JASSO loans
4.1. Policy context
Japan faces a reduced capacity for public financial support forhigher education. The burden of student loans on families is increasing,due either to stagnant household disposable incomes or through exposure to repayment hardship and default. Should Japan continue toshift the cost burden of higher education from the public to private
sources, as is the general trend internationally? And what role, if any, isthere for government policy to manage the trend of shifting the financing burden from parents to the student?
Kobayashi (2017) shows that there has been rising inequality inaccess to university between 2006 and 2016 based on two nationwide
surveys of high school students or their parents: the 2006 CRUMP, HighSchool Student Survey (see Kobayashi & Liu, 2013) and the 2016 Parent
Survey of High School Leavers (see Kobayashi, 2017).
In 2006, only 35% of high school leavers in the lowest income classenrolled in university, compared to 61% in the highest income class.
Enrolment in private universities was highly correlated with income,with the enrolment rate for the highest income group (49.0%) morethan double that of the lowest (23.2%) in this survey. This was not thecase, however, at national and public universities, where enrolments for
all income groups were around 10%.22 National and public universities
contributed to widening access to higher education to low-income
groups by offering relatively inexpensive tuition fees compared to private universities and enrolment.23

How do our simulations perform? In Table 2, we compare earnings
correlations (including zeros) from our panel with earnings simulations
from our t-copula model. We do this for up to three lags of earnings ineach data set using all available observations. This was not possible in
Dearden (2018) as her panel data only involved two earnings observations whereas the Japanese panel data has up to 13 observations
per individual.
The results in Table 2 are very reassuring. Despite only modelingfirst-order rank dependence, the correlations from our simulations
match those observed in our panel data very closely. For the first twolags, the simulated correlations are slightly above the observed correlations, and at lag 3 they are slightly below.

22
Being 9.1% for the lowest income group and 11.9% for the highest income
group.
23
Most national and public universities and colleges are highly selective, but
their missions are to offer the opportunity of higher education to all people.

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This situation appears to have changed, based on data from the2016 Parent Survey of High School Leavers. The enrolment rate inprivate universities continues to be highly correlated with income, as in
the 2006 survey. However, the enrolment rate at national and public
universities and colleges is now also correlated with income, which was
not seen in the 2006 survey. The private university enrolment rate of
the lowest income group is about 28.8%, while that of the highest income group is around 53.6% in the 2016 survey. The enrolment rates atnational and public universities were 10.7% in the lowest income groupand 17.4% in the highest income group. Inequality of access has increased over the decade for public and national universities. The financing burden on both students and households appears to have adversely affected participation in higher education, especially for private
four-year universities and colleges (Kobayashi, 2016).
This pattern of enrolment for the highest achieving students fromfamilies in the lowest income group has also changed. The enrolment
rate of the highest achievers from the lowest income group fell from
65% in 2006 to 62% in 2016, while students in families from thehighest income group rose from 71% in 2006 to 76% in 2016. Enrollingin higher education for high achieving students from families in thelowest income also appears to have become more difficult.
This widening inequality in national and public universities is
consistent with surveys conducted in 2012, 2013, 2016, and 2017 that
confirm the trend (Kobayashi & Wang, 2018). The growth in student
loans from the government, administered through JASSO, has not
succeeded in reducing the inequality of access to higher education(Kobayashi (ed.), 2014).
The inequality of access to university education among family income classes was one of the main reasons for the introduction of a new
grant scheme and partial income contingent loan scheme for undergraduates in 2017. Inequality of access would be a much larger social
issue in Japan without the cultural norm and expectation of support
from parents. But the ability of parents to finance their children's higher
education is becoming more constrained as tuition fees outpace
household disposable income growth (Fig. 3). Further solutions areneeded.

individuals in the 20th percentile of the earnings distribution at eachage. We have 20,000 individuals in our simulations so there will be 200
individuals who fall into the 20th percentile. We choose the 20th percentile as this is typically the point in the distribution on which international comparisons of repayment burdens (RBs) are made. The repayment burden is simply the average student loan repayment forindividuals in that percentile as a proportion of 20th percentile earnings
at each age for males and females. We do this for the simulations withdynamics and with no dynamics in Table 3. It is the latter that is typically done with RB analysis comparisons. Allowing for dynamics does
not affect these calculations in a significant way as those moving in andout of the 20th percentile of the earnings distribution at each age have
similar average JASSO loans and hence repayments. In calculating the
average RB, we cap the top RB at 100% and report this as greater than100%.
We can see from Table 3, that for males in the 20th percentile of theearnings distribution, RBs can be as high as 31% at age 23 but fall tobelow 10% from age 26 onwards. For women, the RBs for those in the20th percentile of earnings stays relatively stable from the ages of 23 to
28 at between 13–20% (which is comparatively low by international
standards) but then dramatically rise and are above 100% from the ageof 31. Recall from Figs. 5 and 6 that at young ages, female graduates inthe bottom half of the earnings distribution earn more than male
graduates (who are more likely to wait for seishain) hence why RBs arehigher for males at very young ages.
Focusing just on individuals in the 20th percentile of the earnings
distribution is somewhat arbitrary given the variation in JASSO loan
repayments and duration. In Table 4 we follow Dearden (2018) andcount how many times over the term of the JASSO loan an individual
faces an “excessive” RB of greater than 18%. The choice of 18% is rather arbitrary but has been suggested in work by Salmi (2003). We
again do this for our simulations with and without dynamics.
The first striking finding from the Table 4, is that if we don't include
dynamics, we underestimate the proportion of individuals facing atleast one period of having an excessive RB. We see that just over 40% ofmale graduates and almost 75% of female graduates face RBs of over
18% at least once during their loan repayment period. If we instead
assumed no earning dynamics, these figures are much lower: 25% formales and 40% for females. We also see that 11% of males and 48% offemales face five or more years of high RBs using our preferred dynamic
earnings simulations.
The above figures illustrate why there has been an increasing problem of JASSO loan default. More than 325,000 borrowers had overdue
repayments on their loans in 2015, up from about 262,000 in 2005. In
2012, JASSO had to sue 6,193 former students for outstanding debts, up
from only 58 in 2004 (Kikuchi, 2018). JASSO measures the default rate
as the number of loan recipients who have repayments that are at least
three months overdue, divided by the total number of borrowers. In
2015, this was 4.2% or approximately 165,000 borrowers in total.
In calculating these RBs we have ignored the fact that JASSO loans
offered since 2014 allow a deferral of up to 10 years of JASSO loan
repayments for low-income borrowers. This deferral, however, is not
automatic and has had quite a low take-up, although the numbers
seeking deferral have risen in recent years.

4.2. Repayment burdens of the current JASSO loan
To look at the repayment burdens associated with the current
JASSO TBRL, we use the detailed distribution of JASSO loans fromJASSO (2014) summarized in Table 1 and allocate loans consistent withthis distribution to our graduate earnings simulations. We assume thatthe amount of loan that a person takes out is negatively correlated with
their lifetime earnings with a correlation of −0.3. As we outlined in
Section 2, the amount of JASSO loans taken out by students is negatively correlated with parental household income. We would, therefore,
expect the JASSO loan amount to also be negatively correlated with
graduate earnings assuming there is some degree of intergenerational
earnings immobility.24 The more negatively correlated the loan is with
graduate earnings, the higher the cost of an ICL. This is important when
we consider the cost of the current Japanese Type 1 ICL loan in
Section 5.
In our simulated sample, the average Type 1 loan for a four-year
degree is 2.23 million yen, with a standard deviation of 0.89 million
yen. This is taken out by 14.2% of students (consistent with the latest
figures for 2016 shown in Fig. 4). The average Type 2 loan taken out fora four-year degree is 3.86 million yen, with a standard deviation of 2.08
million yen, taken out by 24.0% of students. Overall, the average
JASSO loan for our sample is 3.25 million yen with a standard deviationof 1.90. The average payment duration of the loan is 17.5 years.
This allows us to calculate the average repayment burden for

5. Possible directions for reform: universal income contingent
loans
5.1. Introduction
In this section we examine the current JASSO ICL for Type 1 loans
and then suggest ways of improving the design and extending thecoverage of JASSO ICLs. To do this accurately, we must not only estimate graduate earnings but also those of spouses to estimate taxable
income, which is gross earnings minus allowable income deductions as
discussed in Section 2. In our simulations, we model the basic

24
The opposite is true in the US, where the students taking out the highestloans tend to be the highest earners (Dearden, 2018).

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S. Armstrong, et al.

• At the age of 23, virtually all graduates are single, which steadily

Table 3
Average JASSO loan repayments and repayment burdens at the 20th percentileof the age-earnings distribution.

changes until the age of 40. We assume that households do notchange after the graduate is aged 40 (so we ignore divorce, death,etc.).
We allocate spouses by assuming that future spouse's earnings arecorrelated at the age of 23 (before marriage) with a correlation of
0.3 (reflecting some assortative mating).

Age

No Dynamics
Average annual
loan repayment(10,000 ¥)

Male
RB
(%)

FemaleRB (%)

Dynamics
Average annual
loan repayment(10,000 ¥)

Male
RB
(%)

FemaleRB (%)

•

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

18.4
18.4
18.4
18.4
18.4
18.4
18.4
18.4
18.4
18.4
18.4
18.4
18.4
19.4
20.3
20.6
20.6
20.6
24.4
24.4

31.2
15.5
11.1
9.1
8.0
7.3
6.9
6.6
6.4
6.2
6.1
5.9
5.8
5.9
6.1
6.0
5.8
5.6
6.4
6.2

13.7
13.7
14.4
15.6
17.5
20.2
24.3
30.4
> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0

17.8
17.8
16.0
18.5
19.0
17.3
18.7
18.1
20.1
16.3
19.4
18.0
17.5
20.2
21.0
21.6
22.7
22.8
25.5
26.3

30.3
15.0
9.7
9.2
8.3
6.9
7.0
6.5
7.0
5.5
6.4
5.8
5.5
6.2
6.3
6.3
6.4
6.2
6.7
6.7

13.2
13.3
12.5
15.7
18.1
19.1
24.7
29.9
> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0> 100.0

We simulate household earnings of graduates by marriage type andwork out spouse's earnings (the difference between household earnings and the graduate's earnings) once they are married. Once this isdone, we calculate taxable income for males and females at each age.
The JASSO ICL involves graduates paying back 9% per of what weterm taxable income (gross income minus income deductions).
However, the scheme also involves a minimum repayment of 2,000
yen per month (24,000 yen per year) even when a person has no
taxable income. This means that a significant proportion of graduates
face very high RBs with this ICL. Further, graduates can choose
whether they opt for the ICL or TBRL before they graduate. Graduates
who took out low monthly loans of 6,400 yen or less (307,200 yen in
total) would always opt for the TBRL, as monthly repayments under
the TBRL are less than 2,000 yen per month (and hence they are always better off with a TBRL). We estimate that this covers around 7%
of Type 1 borrowers.

Table 4
Measures of years of excessive RBs for JASSO loans.

5.2. Current JASSO ICL loan

Number of years ofexcessive RBs > 18%

Males
No dynamics

Dynamics

No dynamics

Dynamics

0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

73.21
7.84
5.67
2.41
1.61
0.68
0.73
0.52
0.50
0.19
0.33
0.35
0.19
0.17
0.45
0.19
0.38
0.02
1.75
0.00
2.83

58.02
14.30
8.31
4.87
3.23
2.25
1.71
1.38
1.17
0.77
0.47
0.77
0.44
0.47
0.42
0.33
0.42
0.35
0.19
0.05
0.09

58.54
0.76
0.85
0.50
1.70
0.85
2.06
1.18
1.56
2.56
2.41
1.18
2.88
2.38
1.82
1.62
0.50
1.32
4.73
0.26
10.34

25.28
7.93
6.09
6.48
6.00
5.26
5.70
4.49
4.19
3.83
3.62
3.30
3.33
2.76
2.47
2.20
1.72
1.43
1.40
0.74
1.78

We use our simulations to calculate the distributional implicationsof the JASSO ICL loan and compare the case where we assume there areno earnings dynamics and where there are earnings dynamics. We exclude borrowers with a debt of less than 307,200 yen as they will always opt for the TBRL. The distributional and financial implications of
the current Japanese ICL for Type 1 loans is shown in Fig. 10.
A similar exercise was carried out by Kawagoe, Ito, andTakaro (2018)), although they did not use panel data but instead reliedon predicting transitions based on background characteristics using
estimates from the JGSS cross-sectional data (discussed earlier). They
also assumed that all individuals took out a loan of 2.36 million yen,very close to our average Type 1 loan of 2.33 million yen. This means
they could not exclude borrowers who would be better off under the
TBRL. They discounted loan values back to the age of 22, not 18 as we
do in our paper. We discount back to 18 (when the first loan is takenout) as we wanted to calculate the costs of interest subsidies during
university as part of the costs of the loan system. Unlike this paper, they
did not model marriage formation, but instead conducted simulations
assuming that everybody remained single or, alternatively, that everybody married at age 29. They also ignored spousal deductions in
calculating taxable income. Despite these differences, our estimatedcosts of the Type 1 JASSO ICL are reasonably similar. Taking aweighted average of their estimates with a 0.1% discount rate, theycame up with a subsidy of 25.5% with no mobility and 4.3% withmobility.
We calculate that the current Japanese ICL involves a subsidy ofaround 7% using our preferred dynamic simulations. If we assume no
dynamics, the subsidy is estimated to be 14%. The subsidy for the TBRL
version of the JASSO Type 1 loan is 4% with an assumed government
discount rate of 0.33%. This compares favorably with the subsidies
involved in most international ICLs. However, it has two major problems.
Firstly, it is based on taxable income, which makes using employer
withholding for the ICL impossible. Secondly, it involves a minimum
repayment, which means that RBs will be greater than 100% for all
individuals earning below 24,000 yen a year (the ICL minimum repayment) with an outstanding debt.

Females

deduction, employment deduction, and social security deductions forhealth and pensions, as well as deductions for spouses (which dependon both the main earner's salary and their spouse's earnings).
This means that we need to model marriage dynamics. To do this,
we assume that our 9,000 female graduates (45% of all graduates) and
11,000 male graduates (55% of all graduates) will end up in 15,400
graduate household units by the age of 40 (based on marriage formation data for graduates from the LFS). For these households, we makethe following assumptions.

• 51% of female BA graduates and 42% of male graduates will end up
marrying each other (4,600 couples in our simulated sample).
• 25% of male and 24% of female graduates will remain single.
• 32% of male and 25% of female graduates will marry non-BA
partners.

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93%

93%

40

60

80

86%

0

0

20

40

60

% of loan repaid

80

86%

20

% of loan repaid

100Females

100

Males

1 2 3 4 5 6 7 8 9 10All

1 2 3 4 5 6 7 8 9 10All

Decile lifetime earnings

Decile lifetime earnings

No dynamics

Dynamics

Fig. 10. Distributional implications of current JASSO ICL for Type 1 loans.

5.3. An alternative design

borrowers earning below 1.44 million yen per year would pay nothing
under the proposed ICL scheme rather than the minimum 24,000 yen
per year under the current scheme. We follow Barr et al. (2018) andwould not allow people to choose between at TBRL and ICL—only an
ICL would be available.
What are the cost and distributional implications of this alternative
scheme? We see from Fig. 12 that the proposed ICL essentially covers its
costs in full. This is because higher-earning graduates pay around 110%of the loan value in net present value terms and cross-subsidize (insure)the shortfall in repayments from low-earning graduates. The scheme isgenerally progressive, with higher-earning graduates paying the largest
subsidy. For females, we see that with our dynamic simulations, womenin the third and fourth deciles pay slightly more than those in the 5th
and 6th deciles. This is because of our assumption that debt is negatively correlated with lifetime aggregate earnings, so on average
women in these deciles have larger loans. Males on average pay 109%of the loan value and females pay on average just over 84% of the loan(all in net present value terms using a discount rate of 0.33%). If weassume no earnings mobility, the estimated cost of the loan is 19%.

The problems outlined in the previous section could be solved byintroducing employer withholding and basing the ICL repayments on
gross rather than taxable income. Given this is how social security
contributions are deducted in Japan, it should be straightforward for an
ICL and would ensure that repayments were based on contemporaneous
earnings, an essential element of a well-designed ICL (Barr, Chapman,
Dearden, & Dynarski, 2018).
Our proposed ICL scheme has the following elements: a marginal
repayment rate of 9% on gross earnings above 3 million yen per year but
also a lower marginal repayment rate of 5% on gross earnings between
1.44 million and 3 million yen (as a substitute for the minimum repayment in the current JASSO ICL-type loan). We assume a zero interest
rate, which is the interest rate with the current Type 1 loan.
Importantly, we would impose a loan fee or surcharge of 15% to ensurethat the loan is fully self-funding (rather than a minimum charge). This
surcharge is equivalent to a discount to those paying upfront tuition
fees and has been applied in other countries with ICLs (e.g., Australia).
Many countries with ICLs do not have fully self-funding systems andchoose to have subsidies. The size of any subsidy would be a Japanesepolicy choice.25
Fig. 11 shows the repayment schedule for both the current JASSOType 1 loan and our proposed modification. The scatter plot shows therepayments under the current JASSO ICL scheme by gross earnings. The
variation in repayments at different levels of gross earnings is due todifferences in spousal, pension and health insurance deductions forindividuals with the same gross earnings which results in different
taxable income levels and hence ICL repayments.
Under our scheme, a person borrowing 2.4 million yen would have adebt of 2.76 million yen after the 15% fee or surcharge is applied. Their
repayment schedule would depend on their gross earnings and would
continue until the debt is discharged or they retire or die. Under thisscheme, a graduate earning 4 million yen a year would pay
0.05*(3,000,000–1,440,000) + 0.09*(4,000,000–3,000,000) yen peryear, which amounts to 168,000 yen per year. From Fig. 11, we see that
this is very similar to what the same person would pay under the current JASSO ICL. However, for earnings above 4 million yen a year,
borrowers would pay progressively more than under the current ICL,
and for earnings below 4 million yen a year, progressively less. All

5.4. A universal ICL for Japan
Finally, we model a universal ICL loan. To do this, we assume thatthe average loan taken out by students is 3.64 million yen over four
years and that those currently not eligible for JASSO loans can take out
the full range of JASSO loans. Hence the simulations here involve
higher average loans than in the earlier simulations, which focused on
Type 1 loans only (an average loan of 3.64 million yen instead of 2.33
million). Again, we assume the size of the loan is negatively correlatedwith lifetime earnings. We impose a 0.33% interest rate for those taking
out Type 2 loans which applies only after graduation. The results ofdoing this are shown in Fig. 13.
We see that even with significantly higher average loans, the proposed ICL is essentially self-funding. We calculate that 96% of the costs
are recovered.26 This is very similar to the subsidy with the current
JASSO TBRL (which has a small interest subsidy during university for
all students, and for the term of the loan for Type 1 loans). Clearly, thisis just one possible type of universal ICL – others with similar subsidies
could be designed with different distributional implications (seeBarr et al. (2018)).

25
See Britton, van der Erve, and Higgins (2018) for a discussion on subsidies
and international comparisons.

26

12

If we assume no dynamics, the estimated subsidy is 21%.

Economics of Education Review xxx (xxxx) xxx–xxx

60
40
20
0

Annual ICL repayment (10,000 yen)80

S. Armstrong, et al.

144 200

300
400
600
Annual Gross Earnings (10,000 yen)
JASSO ICL

800

1000

Proposed ICL

Fig. 11. Repayment schedule for JASSO ICL and Alternative ICL: Type 1 loans only.

100
80

81%

40
20

40

60

81%

% of loan repaid

100

99%

60

99%

80

Females0020% of loan repaid

Males

1 2 3 4 5 6 7 8 9 10All

1 2 3 4 5 6 7 8 9 10All

Decile lifetime earnings

Decile lifetime earnings

No dynamics

Dynamics

Fig. 12. Distributional implications of alternative ICL: Type 1 loans only.

80
60
20

% of loan repaid

79%

0

20

40

60

79%

96%

40

80

96%

0

% of loan repaid

100Females

100

Males

1 2 3 4 5 6 7 8 9 10All

1 2 3 4 5 6 7 8 9 10All

Decile lifetime earnings

Decile lifetime earnings

No dynamics

Dynamics

Fig. 13. Modeling a universal ICL.

13

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S. Armstrong, et al.

6. Conclusions

conference held on 4 October 2017 at International House, Tokyo. The
authors are also grateful to the Research School of Economics at theAustralian National University and Kazumasa Iwata and Japan Center
for Economic Research for their support. The authors are grateful to
Sam Hardwick for excellent research assistance and project support.
Lorraine Dearden would like to gratefully acknowledge financial assistance received from the ESRC-funded Centre for the Microeconomic
Analysis of Public Policy at IFS (grant RES-544-28-5001) and theHEFCE and ESRC funded Centre for Global Higher Education at
UCL–IOE (Grant no. ES/M010082/1). Nobuko Nagase would like togratefully acknowledge financial assistance received from the Japan
Society for the Promotion of Science fund (KibanC15K03503), and also
by the Joint Usage and Research Center Programs of the Institute of
Economic Research, Hitotsubashi University. Permission to use themicrodata of Japanese Labor Force Survey was obtained through the
Joint Usage and Research Center Programs on the basis of the Statistics
Act (Act No. 53 of 2007), Article 32. The Japan Household Panel Survey(JHPS/KHPS), was kindly provided by the Keio University Panel Data
Research Center.

This paper highlights many of the problems with the current JASSO
student loan system. We have used LFS data in combination with JHPS/
KHPS panel data to help understand the reasons behind the current
problems with JASSO student loans. We have highlighted the importance of not only understanding and considering the distribution of
earnings of graduates at each age but also modeling graduate earnings
dynamics.
One key issue identified is the unique nature of the Japanese labormarket compared to other countries operating ICLs. In particular, thelow earnings of female university graduates, once they get married
and/or have a child, raises interesting design issues. These low earnings
appear to be driven in part by firm, tax and social security policies thatgive 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. However, it is likely to remain a feature of the Japanese
graduate labor market for some time.
We argue that most of the problems with the current JASSO loansystem could be solved in a fair and efficient way by introducing auniversal ICL. The unusual features of the Japanese graduate labormarket mean that the parameters of the loan need to be very different
from those operating in the United Kingdom and Australia. In particular, to minimize government costs there must be significantly lower
repayment thresholds coupled with incremental rises in marginal repayment rates rise as earnings rise. A loan surcharge is probably alsoneeded to reduce taxpayer subsidies and to ensure only those who needloans take them out.27 This is to ensure that females early in their career
make a significant repayment contribution before they get married andthat those with relatively low earnings when married make some further modest repayments. The changing nature of the female labormarket, which is evident in more recent cohorts, will also help.
Importantly, the availability of universal loans needs to be restricted
to high-quality university and college provision for suitable students ina transparent way. This is always much more difficult in a country
where most students go to private universities. This is part of a broader
problem with the current Japanese loan system and requires careful
thought.
JASSO student loans are available to both two-year college as well
as four-year university students and future work needs to ensure thatany ICL design would also work for two-year college graduates taking
out loans. Given the relatively low repayment thresholds we are proposing, it seems highly likely that this would not pose a problem given
the lower debts associated with two-year college. While they have notbeen considered in our paper, it would be relatively simple to include
this in future work.
Finally, we have shown that incorporating realistic dynamics is
crucial to developing a self-sustaining universal student loan systemthat is equitable, affordable and ensures that all deserving students cantake full advantage of post-high school education in Japan without any
financial barrier. Given recent evidence of increasing inequality in access by household income, this seems very important.

Supplementary materials
Supplementary material associated with this article can be found, inthe online version, at doi:10.1016/j.econedurev.2018.10.012.
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