Quantitative analysis of rent arrears in private rental
housing in Japan
Takeshi SO† and Yuta ARAI
Housing Institute, Recruit Sumai Company Ltd.
Nittobo Bldg, 2-8-1 Yaesu, Chuo-ku, Tokyo, Japan†e-mail:so@r.recruit.co.jp
Abstract—This study is the first large-scale quantitative analysis ofprivate rental housing rent arrears in Japan. The study data arefrom the Leasing Information Communication Center (LICC),
which operates a private rental housing rent arrears information
database. There are 728 759 data items used in this study, which is
the largest scale with the smallest bias. This study aims to provide
analysis results required for the discussion of a housing safety net
and social loss due to rent arrears. We define new indicators of rent
arrears and analyze them. The main findings are as follows. First,
the rent arrears rate is about 3%, and in particular, long-term rent
arrears are a serious issue for lessors. Second, 0.73% of contracts forlong-term rent arrears account for 67% of the total loss. Smalllessors cannot always accept loss of long-term rent arrears. Third,social loss due to rent arrears is estimated to be about 68.3 billion
yen in Japan. Serious rent arrears do not occur very infrequently,
but bring great loss to lessors once they arise. Small-scale lessors areaffected more by rent arrears than others. Rent arrears are a social
problem that must be solved in Japan.
Keywords-private rental housing; rent arrears; housing safety net;credit information

Japan Property Management Association Research Institute [2]conducted a survey on the rent arrears rate, but it did not include
a specific monetary scale or the results of detailed quantitative
analysis. Thus, there is no previous research using large-scalequantitative analysis on private rental housing rent arrears.
Among the reasons why there is no previous research is thefact that a large volume of data on rent payments that includes
sufficient information on the attributes of people entering into
rental contracts (hereafter, “renters”) based on unified criteria has
not been accumulated. Even though housing construction-relatedcompanies possess hundreds of thousands of rental contracts, rent
settings and renter attributes are assumed to be within apredetermined

range

as

the

designsofbuildings

arecomparatively homogeneous.
B. Discussion on rent arrears

I. INTRODUCTION
A. Research background and previous researchWithin this context, various policy debates on rent arrears havetaken place without any sort of quantitative evaluation.

After the Lehman Brothers Shock of 2008, a large number ofWith regard to private rental housing rent arrears, Nakano [3]haken-giri (layoffs of temporary employees dispatched to

noted that, “Since the unrecovered rent rate is only about 0.01%

companies by staffing agencies) were carried out and a Kosetsu

of the total, the amount of unrecovered money that is passed on to

Hakenmura (Public Village for Temporary Workers) was opened

renters is insignificant.” On the other hand, the Council for Social

in Hibiya Park, rent arrears in private rental housing were

Infrastructure [4] stated, “The increase in arrears costs from one

recognized clearly as a social problem in Japan. Subsequently,

group of people who are repeatedly and continuously in arrears

newspapers frequently reported cases of people who lost theirthat is borne by the many other renters in the form of higher rent

homes through illegal evictions. In response, in February 2009,and guarantee fees has become a problem from the perspective of

the Ministry of Land, Infrastructure, Transport and Tourism

fairness, and it is important to take a viewpoint for the benefit of

prepared documents from Tokyo for industry groups requesting

renters as a whole.”business optimization and in March 2010, this request was
submitted to the Diet under the Residence Stabilization Act.
In this field, the only research into the actual conditions of rent
arrears is essentially Hirayama [1], which focuses on rent arrears
in public housing. In terms of surveys by industry groups, theMoreover, Kikuchi [5] pointed out that, “It is possible toconsider public funding and the financing system for guarantees
for rent arrears among elderly and disabled households to be apart of social security benefits.”

private companies, there are many housing construction-related

C. Research objective
If the actual situation of private rental housing rent arrears
could be clarified quantitatively, it would be possible to progress
the various abovementioned discussions. Therefore, the objective

companies and, as a result, bias is due to their building
specifications and construction areas.
Conversely, the data registered by the LICC is from 13of this research is to clarify quantitatively such variables as theguarantee

rate of occurrence of rent arrears, the ratio of long-term rent

companies, and there are tens of thousands of data items on realarrears to total rent arrears, and differences in arrears rates

estate companies and landlords, which are the LICC’s businessaccording to rent band, gender, age, and other factors.

partners. Thus, the LICC database has more data items than evencompanies,

includingseveral leadingindustry

It is considered that Japan is approaching a phase in which it

the top ranking company in the private sector, and therefore, there

will have to reconstruct its safety net owing to the future aging ofis comparatively little bias in the database, which can be

the population and widening of the income gap. In this context, it

considered a representative database that has been unified to ais considered that the results of a quantitative analysis of private

standard able to withstand quantitative evaluation.

rental housing rent arrears would contribute significantly topolicy creation by providing the basic facts that it requires.

Prior to the analysis, data cleansing was carried out, including
to remove items with addresses that could not be processed
normally. As a result, the numbers of targeted data items were as

II. FRAMEWORK FOR EMPIRICAL ANALYSIS OF RENT

follows: 728 759 rental contracts, and 11 .4 million subrogation

ARREARS

payment data (in principle, monthly rental contracts), giving an
average of 15.6 items per rental contract. Public housing was not

A. DataThis research uses data registered in the private rental housing

rent arrears information database provided by the Leasing
Information Communication Center (LICC)[6].

included in this data.
There are around 13.36 million private rental properties withresidents in total nationwide, according to the Statistics Bureau of

In addition to the number of data items on public housing,
Urban Renaissance Agency (UR) public corporation housing, andthe Ministry of Internal Affairs and Communications [7], whichis 5.5% of the number of targeted data items.

provided by the LICC for the top 10 ranked private rental housing

The first month of tenancy for the target data (the first month

management companies, Table I shows the number of managedof the guarantee contract) was set as March 2010, and the lastproperties by 13 management agencies, and the ratios of rented

subrogation

properties and privately rented properties as percentages of the

December 2012, meaning there were at most 34 months from thetotal .

start of tenancy.

There is clear bias in the attributes of the renters of public
housing and UR Public Corporation housing, while among

payment

information

registration

Management agency (company

No. of managed properties

while the number of targeted rental contracts was less than 100
Ratio of total rental properties

Ratio of private rental properties

1 Public Housing

2,089,000

11.8%

-

2 UR Public Corporation

918,000

5.2%-

3 LICC730,206

4.1%

5.5%

4 Daito Trust Construction

694,205

3.9%

5.2%

5 Leopalace 21556,207

3.1%

4.2%

6 Sekisui House Group

489,967

2.8%

3.7%

7 Starts Group

319,767

1.8%

2.4%

8 Daiwa Living

297,948

1.7%

2.2%

9 Able192,309

1.1%

1.4%

10 Housemate Group

170,657

1.0%

1.3%

11 Minitech (MiniMini)

166,260

0.9%

1.2%

12 Token Corporation

153,936

0.9%

1.2%

13 Taisei Housy Group80,0580.5%

0.6%

Total number of rental properties

17,700,000

Total number of private rental pro

13,366,000

Ratio of private rental properties

75.5%

as

The regional distribution includes data on all 47 prefectures,

TABLE Ⅰ. NUMBER OF MANAGED RENTAL PROPERTIES BY MANAGEMENT AGNCY
Rank

month

only for Shimane Prefecture and less than 1 000 only for Fukui

as the denominator is in many cases calculated only from

Prefecture and Yamanashi Prefecture.

contracts during the tenancy period. However, this research

A condition of becoming a member of the LICC isincludes not only contracts still in the tenancy period, but also

membership of the Rent Guarantee Operators Council (hereafter,

contracts that have been completed already. Next, the arrears loss

“the Council”) of the Japan Property Management Association

rate is defined as follows:(JPMA).
Members of the Council are obliged to comply with voluntaryrules for business optimization that the Council has established,

Arrears loss rate ＝ cumulative arrears amount / cumulative rent
amount.

and therefore, it is considered that this data is not affected by ashortening of the arrears period by illegal evictions or other suchfactors.

The arrears loss rate expresses the ratio of the cumulative
arrears amount relative to the cumulative rent amount, and themonthly cumulative rent amount is the original rental contract

B. Definitions of indicators
In many cases, the payment deadline for monthly rent is the
25 of each month. Therefore, even supposing that a person is inthamount, including common area expenses, multiplied by the
number of elapsed months. Next, the number of arrears months isdefined as follows.

arrears, in many cases, the arrears are eliminated quickly. A
characteristic of arrears is that even if there is a large amount of

Number of arrears months ＝ cumulative arrears amount /arrears at the start of the month, by the end of the month, this has

initially contracted monthly rent.

been paid, and thus, both the arrears rate and monetary arrears
amount fluctuate greatly within the period of a month.

The number of arrears months generally is considered to

In addition, a feature of rent arrears as a monetary debt is that

express the arrears period, but it is not necessarily the case that

unlike housing loans and cash loans, in which the total amount ofarrears are always continuous. Therefore, the cumulative arrears

debt is fixed at the time of borrowing, if arrears continue, then theamount expresses the amount corresponding to the total amount

total debt increases without limit until the debt is cleared.

for the number of arrears months from the initially contracted

As there are no accepted definitions for the indicators of rent

monthly rent amount, including common area expenses. The

arrears, upon considering the above characteristics, we newly

number of arrears months is rounded down when the period isdefined the indicators as follows:

more than 1 month and rounded up when it is less than 1 month.
However, an arrears monetary amount of less than 10 000 yen is

Number of elapsed months ＝ number of months of tenancy,with the month the tenancy began as zero.

considered to correspond to zero arrears months.
It is important to have a record date, as the numerical values
for the arrears rate, arrears loss rate, and number of arrears

The reason why the month the tenancy began is set as zero ismonths differ greatly between the beginning and the end of thethat generally, the rent for the first month is paid in advance at themonth. In this research, the record date is set as the 20th of eachtime of entering into the rental contract, and so, it is considered

month from the LICC’s data registration regulations.

that rent arrears practically never occur for this month. The
arrears rate is defined as follows:

III. EMPRICAL ANALYSIS
A. Number of data items by prefecture and basic rent statistics

Arrears rate ＝ number of cases of arrears / number of rental
contracts.

Table II shows the number of targeted data items by prefecture
and basic statistics related to rent. The number of data items
excluded by the data cleansing was an extremely small number,

Generally, the number of rental contracts with the arrears rateor 1.41% of the total.

TABLE Ⅱ. NUMBER OF DATA ITEMS ACCORDING TO PREFECTURE AND RENT BASIC STATISTICS
Data
Prefecture

Rent

No. of items

Data

Ave

SD

Min

Max

No. excluded

Hokkaido

14,80048,682

17,96010,000119,750

224

Exclusion rate
1.49%

Aomori Prefecture

3,236

44,853

12,642

15,00088,000

37

1.13%
0.99%

Iwate Prefecture

7,073

43,517

12,49313,00089,50071

Miyagi Prefecture

18,17048,581

16,062

10,000108,400

237

1.29%

Akita Prefecture

4,379

43,963

11,431

10,00079,00071

1.60%

Yamagata Prefecture

2,707

47,021

13,68512,00089,00015

0.55%

Fukushima Prefecture

4,959

44,02912,213

10,00089,00080

1.59%

Ibaraki Prefecture

7,087

50,12315,08413,00099,00074

1.03%

Tochigi Prefecture

3,951

48,555

14,56415,00099,52548

1.20%

Gunma Prefecture

5,712

46,58012,873

10,00089,00038

0.66%

Saitama Prefecture

28,343

61,94919,493

14,780129,500

340

1.19%

Chiba Prefecture

43,20660,20020,401

11,000129,800

525

1.20%

Tokyo

101,691

90,44937,331

10,000239,600

1,777

1.72%

Kanagawa Prefecture

36,72972,80526,87910,000169,700

525

1.41%

Niigata Prefecture

1,668

48,271

14,621

12,00095,0009

0.54%

Toyama Prefecture

1,961

48,518

12,236

17,20088,00015

0.76%

Ishikawa Prefecture

4,037

49,052

14,308

10,40099,00030

0.74%

Fukui Prefecture

554

50,42814,017

10,00099,0503

0.54%

Yamanashi Prefecture

717

49,36913,531

19,00088,15011

1.51%

Nagano Prefecture

1,029

50,03813,787

15,00098,00014

1.34%

Gifu Prefecture

2,049

53,932

12,95615,00099,63024

1.16%

Shizuoka Prefecture

4,108

58,234

14,862

18,400109,000

41

0.99%

Aichi Prefecture

27,24061,806

17,47514,000129,900

451

1.63%

Mie Prefecture

2,867

52,971

14,18719,00097,95012

0.42%

Shiga Prefecture

4,567

52,413

13,924

14,05098,000

75

1.62%

Kyoto

20,15260,61019,292

10,000129,970

339

1.65%

Osaka prefecture

77,98162,80922,06010,000149,800

1,388

1.75%

Hyogo Prefecture

29,12061,067

20,152

10,000139,900

583

1.96%

Nara Prefecture

2,905

51,904

18,55910,000119,000

43

1.46%

Wakayama Prefecture

1,576

50,654

12,642

16,50089,00013

0.82%

Tottori Prefecture

1,390

47,335

12,24020,00088,0007

0.50%

Shimane Prefecture

82

55,232

6,155

45,00069,5000

0.00%

Okayama Prefecture

12,10348,384

14,282

10,00099,000125

1.02%

Hiroshima Prefecture

17,00048,965

15,604

11,00099,000253

1.47%

Yamaguchi Prefecture

1,461

51,278

14,112

15,00092,5758

0.54%

Tokushima Prefecture

3,484

46,053

13,197

11,50088,00026

0.74%

Kagawa Prefecture

4,660

45,484

13,73914,00088,00033

0.70%

Ehime Prefecture

6,855

47,31912,913

10,25089,800

41

0.59%
0.62%

Kochi Prefecture

1,606

44,89912,58014,00089,00010

Fukuoka Prefecture

110,563

49,87816,35410,000109,950

1,627

1.45%

Saga Prefecture

5,019

49,063

12,47415,00088,80053

1.04%

Nagasaki Prefecture

10,70048,185

13,89414,00089,150114

1.05%

Kumamoto Prefecture

20,46747,247

13,697

12,00089,500257

1.24%

Oita Prefecture

18,68847,057

13,727

10,00089,900230

1.22%

Miyazaki Prefecture

14,24743,323

12,441

10,00089,000115

0.80%

Kagoshima Prefecture

6,383

46,148

13,101

10,00088,00071

1.10%

Okinawa PrefectureAll

29,477

49,83913,472

10,00099,800349

1.17%

728,759

59,70926,025

10,000239,600

10,432

1.41%

SD indicates the standard deviation

The maximum rent value is generally around 100 000 yen

for each of the elapsed months.

outside of the three major metropolitan areas, and the maximum

The arrears rate becomes stable after reaching around 3.5%

value in Tokyo is 239 600 yen, which is within the general rent

after 12 months. Immediately after the start of tenancy, the arrears

band.

loss rate rises to 1.7%, but over the passage of some months, it
converges at about 0.6%. The fact that the arrears loss rate does

B. Arrears rate and arrears loss rate
Fig. 1 shows the trends in the arrears rate and arrears loss rate

not decline even as the number of months elapsed increases
indicates that the arrears amount is increasing. In other words,this shows that some people in arrears who continue to reside oncontinual arrears and also a state in which it is very highly likely

the properties remain in arrears, or that some do not repay theirthat the principle of the breakdown of trust, which is thearrears even after leaving the properties.

condition for the contract to be cancelled, will be applied to the

An arrears loss rate of around 0.6% does not include personnel

rental contract. Seven months of arrears is the shortest possible

costs for issuing reminders and other costs, and so, the actual costtime for the completion of forced payment following legal

incurred by the landlord may be several times this amount.

proceedings and a legal ruling in the event that the rental contract

In addition, while it is not shown in Fig. 1, the arrears rate ofrenters during their tenancy period peaks approaching the
12-month point at around 2.7%.

was cancelled after 3 arrears months and the landlord
immediately initiated legal proceedings.
After reaching 3.5% after 12 months, the total arrears rate

This is lower than the 3.3% from the arrears amount rate at theessentially stays as this level, and the rates of arrears of 4 months

end of 1 month in the JPMA survey for the first half of 2012 (as itor more and of 7 months or more rises alongside the increase inis 1 month’s arrears, it can be considered to be essentially thethe number of elapsed months. After 24 months, the rate ofsame as the arrears rate. Thus, the arrears rate obtained from thearrears of 4 months or more is 0.73% and of 7 months or more isdata used in this study may be lower than the arrears rate for the

0.4%.

market as a whole.

This indicates that while the total arrears rate does not change
significantly, the content of the arrears has deteriorated. In other

C. Arrears rate for long-term arrears

words, while the number of people in arrears has not increased,

Fig. 2 shows the trends for each elapsed month in the total arrears

among those in arrears, there is an increasing rate of those inrate and the rates for arrears of 4 months or more and 7 months

arrears for a large number of months.
D. Ratio of long-term arrears to total arrears
Fig. 3 shows the trends in the ratio of the arrears amounts of 4months or more and 7 months or more relative to the total arrears
amount for each of the elapsed months.
After 24 months, the arrears amount of 4 months or moreconstitutes 60.8% of the total arrears amount, and after 30 months,
it reaches 67.3%. Similarly, after 24 months, the arrears amountFigure 1. Trends in the arrears rate and arrears loss rate.

of 7 months or more constitutes 43.3% of the total

Figure 3. Trends in the arrears amount rate and ratio of arrears of 4 months or
Figure 2. Trends in the total arrears rate and the rates for arrears of 4 months

more and 7 months or more relative to the total arrears amount.

or more and 7 months or more.

arrears amount, and after 30 months, has reached 49.5%.
or more.
Arrears of 4 months or more involve a state of repeated andThis constitutes the majority of the arrears amount from thosepeople who are repeatedly and continually in arrears, which inFig. 2 was a negligible amount of less than 1% of the total.

objective variable being whether 3 months of arrears had been

As described in Subsection III.B, if seen from the average,

reached, as this is the time generally considered for relations of

there is a loss of about 0.6% for lessors, but it is not the case thattrust between the renter and landlord to have been broken. This

all lessors incur a loss of around 0.6%.

means the condition for the cancellation of the contract has been

In private rental housing, privately owned properties constituteapproximately 85% of the total, 60.4% of the private landlords

met, with the rent band, gender, and age group as the explanatory
variables and prefecture of residence as the dummy variables.

are aged 60 years and older, while 28.3% of landlords own 10

In addition, as the difference in rent between regions is large,

properties or less and 55.1% 20 properties or less, meaning there

the regions of analysis were set as Saitama Prefecture, Chiba

are many elderly micro-manager landlords.

Prefecture, Tokyo, and Kanagawa Prefecture. Furthermore, as the

In

the

case

of

investment corporations andrelatedarrears rate changes according to the number of months elapsedorganizations that own several hundred rental properties, a loss

from the start of tenancy, the period of analysis was set as more

due to rent arrears can be leveled out completely. However, in thethan 24 elapsed months.

case of small-scale managers, such as individual landlords

Table III shows the rent- and age-related descriptive statistics.

owning eight properties, even though the group of people who

As Tokyo’s average rent is high and the standard deviation is also

are repeatedly and continually in arrears constitute less than 1%,

large, the maximum rent is also high, at slightly less than 240 000

once a person becomes repeatedly and continually in arrears, theyen.

arrears amount after 12 months is equivalent to 1 year’s worth ofarrears, which is 12.5%, of the total rent. This cannot be
described as a small amount, both in terms of economic andTable IV shows the results of the binomial logistic regression
analysis.
With regard to age, the baseline was 40–44 years, which
includes the average age; with regard to rent, the baseline was thepsychological impact on landlords.

70 000 yen range, which includes the average rent; with regard togender, the baseline was females; and with regard to prefectures,

E. Results of logistic regression on occurrence of rent arrears
Various reasons can be considered for why rent arrears occur,

the baseline was Tokyo. The coefficients of determination

but the research has been insufficient. The data used in thisadjusted for the degree of freedom were 0.016 in Tokyo and theresearch do not include information on renters’ attributes, such as

three prefectures, 0.018 in Tokyo, 0.020 in Kanagawa Prefecture,

their family situations, annual income, and occupations, and0.037 in Saitama Prefecture, and 0.019 in Chiba Prefecture. All

consequently, a full analysis was not possible. However, anthese values are extremely low and the explanatory variables used

analysis was carried out using rent, region, age, and gender,

in this research have very low explanatory power for whether

which were included in the data.

there were arrears of 3 months.

A binomial logistic regression analysis was carried out with the
TABLE III. RENT AND AGE DESCRIPTIVE STATISTICS

Rent
Tokyo and 3 prefectures
Tokyo
Kanagawa Prefecture
Saitama Prefecture
Chiba Prefecture

Ave
78,741
91,90873,44562,61160,824SD

Age
Tokyo and 3 prefectures
Tokyo
Kanagawa Prefecture
Saitama Prefecture
Chiba Prefecture

Ave

SD

40.2
39.7
41.2
40.6
40.4

33,88137,70826,47019,341
20,258

12.8
12.5
13.1
13.2
12.9

Min
10,00010,00013,00014,78014,000MinMax
239,600
239,600
169,000
129,000
129,700

No. of items
61,681
30,612
11,117
7,433
12,519Max
No. of items
20
93
61,68120
93
30,61220
90
11,117
20
91
7,433
20
93
12,519SD indicates the standard deviation.

TABLE IV. RESULTS OF BINOMIAL LOGISTIC REGRESSION ANALYSIS■Binomial logistic regression of arrears of one of Tokyo's three prefectures
Objective variable: whether or not rent arrears has reached 3 months. If yes, ＝1
Explanatory variable

Tokyo and 3 prefectures
Kanagawa Pref.

Tokyo

Saitama Pref.

Chiba Pref.

odds ratioSEodds ratioSEodds ratioSEodds rtioSE

odds ratio

SE

Rent 2 million level dummy

2.31 ***

0.54

2.23 *

1.06

2.58 *

1.28

3.75 ***

1.57

1.02

0.63

Rent 3 million level dummy

1.87 ***

0.24

1.23

0.35

2.13 ***

0.55

1.95 **

0.62

2.15 ***

0.57

Rent 4 million level dummy

1.67 ***

0.19

1.50 **

0.30

1.25

0.32

1.86 **

0.51

2.08 ***

0.52

Rent 5 million level dummy

1.47 ***

0.15

1.28

0.21

1.21

0.28

1.60 *

0.44

2.01 ***

0.50

Rent 6 million level dummy

1.23 **

0.13

1.09

0.17

1.11

0.26

1.15

0.33

1.82 **

0.46

Rent 7 million level dummybaselinebaselinebaselinebaselinebaseline

Rent 8 million level dummy

1.21 *

0.14

1.32 *

0.20

1.34

0.32

0.61

0.26

0.95

0.33

Rent 9 million level dummy

1.44 ***

0.17

1.78 ***

0.27

1.03

0.31

0.48

0.26

1.08

0.43

Rent 10 million level dummy

1.81 ***

0.23

2.13 ***

0.34

1.29

0.40

1.50

0.71

1.18

0.55

Rent 11 million level dummy

0.95

0.17

1.23

0.25

0.63

0.30

Rent 12 million level dummy

1.31

0.22

1.65 *

0.32

0.54

0.33

Rent 13 million level dummy

1.63 ***

0.30

1.75 ***

0.37

1.30

0.63

(omitted)(omitted)

Rent 14 million level dummy

1.05

0.25

1.13

0.31

0.88

0.54

(omitted)(omitted)

Rent 15 million level dummy

1.40

0.31

1.53 *

0.38

0.94

0.70

(omitted)(omitted)

Rent 16 million level dummy

2.57 ***

0.52

2.97 ***

0.66

0.71

0.73

(omitted)(omitted)

Rent 17 million level dummy

1.66 *

0.47

1.80 **

0.53(omitted)(omitted)(omitted)

Rent 18 million level dummy

1.50

0.50

1.61

0.55

(omitted)(omitted)(omitted)

Rent 19 million level dummy

3.07 ***

0.92

3.27 ***

1.01(omitted)(omitted)(omitted)

Rent 20 million level dummy

2.22 **

0.75

2.40 **

0.83(omitted)(omitted)(omitted)

Rent 21 million level dummy

1.59

0.74

1.73

0.81

(omitted)(omitted)(omitted)

Rent 22 million level dummy

1.71

0.88

1.84

0.96

(omitted)(omitted)(omitted)

Rent 23 million level dummy

1.26

0.75

1.36

0.81

(omitted)(omitted)

Gender _ male dummy

1.80 ***

0.11

1.82 ***

0.16

Gender _ female dummybaselinebaseline

1.69 ***

0.26(omitted)
0.84

2.32 ***

baseline(omitted)
0.87(omitted)(omitted)
0.47

baseline

1.79 ***

0.27

baseline

Age 20–24-year-old dummy

1.27 *

0.16

1.65 ***

0.30

1.23

0.38

1.06

0.37

0.83

0.24

Age 25–29-year-old dummy

0.88

0.08

1.08

0.14

0.74

0.17

0.80

0.21

0.61 **

0.13

Age 30–34-year-old dummy

0.72 ***

0.07

0.88

0.11

0.48 ***

0.12

0.53 **

0.15

0.64 **

0.13

Age 35–39-year-old dummy

0.78 **

0.08

0.78 *

0.11

0.88

0.20

0.75

0.21

0.71

0.15

Age 40–44-year-old dummybaselinebaselinebaselinebaselinebaseline

Age 45–49-year-old dummy

0.98

0.10

1.12

0.17

0.95

0.23

0.95

0.28

0.75

0.19

Age 50–54-year-old dummy

1.01

0.11

1.10

0.18

0.93

0.25

1.02

0.31

0.87

0.21

Age 55–59-year-old dummy

0.75 **

0.10

0.89

0.16

0.89

0.25

0.54

0.21

0.47 **

0.15

Age 60–64-year-old dummy

0.67 ***

0.10

0.79

0.16

0.68

0.22

0.60

0.24

0.48 **

0.16

Age 65–69-year-old dummy

0.81

0.13

0.90

0.22

1.14

0.37

0.35 *

0.21

0.64

0.24

Age 70–99-year-old dummy

0.41 ***

0.10

0.61

0.20

0.45 *

0.22

0.20 **

0.15

0.23 **

0.14

Residence _Saitama Pref. dummy

0.89

0.08

Residence _Chiba Pref. dummy

0.78 ***

0.06

Residence _Kanagawa Pref. dummy

0.87 *

0.06-4.34 ***

0.16

-4.04 ***

0.26

-4.30 ***

0.33

-4.31 ***

0.28

Residence _ Tokyo dummy
Constant termbaseline
0.02 ***

0.00***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively
SE represents the standard error
likelihood

-7246

-3756

-1245

-853

-1344

Number of samples

61,681

30,612

11,117

7,343

12,192

Looking at the effects according to rent band, in Tokyo and thethree prefectures, significantly positive effects were observed inat the 80 000, 90 000, 100 000, 130 000, 160 000, 170 000, 190
000, and 200 000 yen levels.

the baseline of total rent of less than 70 000 yen. In the rent bands

However, Tokyo and the three prefectures showed different

above the baseline, there were also significantly positive effects

trends when viewed according to prefecture, and positive effects

above the baseline rent band were seen only for Tokyo, whilearrears, personnel costs, and other costs, such as for legal

Kanagawa Prefecture, Saitama Prefecture, and Chiba Prefecture

processing.

were not classified as having positive effects in the rent bands

The total arrears are not what are incurred on an average basis,

above the baseline. The results according to gender show it is

but what are incurred from some people repeatedly andhighly likely that overall, there are more men than women incontinually being in arrears. It is highly likely that thearrears of 3 months or more.

management of small-scale landlords is affected greatly by

For the results according to age, in Kanagawa Prefecture,
Saitama Prefecture, and Chiba Prefecture, negative effects werepeople who are repeatedly and continually in arrears, who theyoccasionally encounter.

observed in the 30–34 year group and the 70–79 year group.

In addition, the total arrears rate is around 3.5% and rent

In addition, there were clear differences according to place ofarrears are by no means rare. Moreover, there have been instances

residence; compared to the baseline of Tokyo, negative effects

of murders due to rent arrears and the psychological burden thatwere observed in Chiba Prefecture and Kanagawa Prefecture,

rent arrears places on landlords is considerable.

suggesting the arrears rate in Tokyo is high.

Individual landlords are able to avoid risk, including thispsychological burden, by using rent guarantee companies, and

IV. CONCLUSION

this usage is increasing. As of 2010, their use rate was around

The total rent arrears rate starts to increase immediately after

27% and annual sales for the industry as a whole had reached 50

the start of the rental contract, then, after 12 months, reaches

billion yen.

3.6%, and subsequently, stays around this level. Arrears of 4

As in most cases tenants have to pay the fees of the rent

months or more constitute 60.8% of the total after 24 months, andguarantee company, it can be said that the cost of rent arrears dueby 30 months, have reached 67.3%, when the arrears rate is

to some persons repeatedly and continually being in arrears is

0.77%. After 24 months, arrears of 7 months or more constituteimposed on the majority of tenants, who themselves do not fall

43.3% of the total arrears amount, reaching 49.5% after 30

into arrears.

months, when the arrears rate is 0.45%.

In this research, it was not possible to carry out a full analysis

Thus, we understand that the arrears amount of those peopleof differences in rent arrears according to regions or the attributes

who are repeatedly and continually in arrears increases over time.

of renters. Neither was it possible to analyze fully why people fall

From the results of the binomial logistic regression analysis,

into arrears. Thus, these are considered topics for future research.

positive effects were observed in Kanagawa Prefecture, Saitama

In addition, there is considered a need for research on

Prefecture, and Chiba Prefecture in the rent band below themethodologies about whether it is possible in some way tobaseline, strongly suggesting the possibility that a large amountsuppress rent arrears, as well as research findings for policyof rent arrears occurs in the low rent bands. However, theissues, such as ways of constructing a housing safety net for

explanatory power of this variable was weak and the relationshippeople who may need secure housing when moving into low-rent

with income was not clear, and thus, it is considered highly

properties, and ways of eliminating the so-called information

possible that there are factors behind rent arrears other thanasymmetry problem.

income.
The private rental housing rent arrears amount does notconverge over the passage of time and instead increases, and if
looking from the average, it is around 0.6% of the rent eachmonth.
When roughly calculated from a total of 17.7 million

ACKNOWLEDGMENT
We wish to express our appreciation to the LICC, which
provided valuable data for this research. Even as its members
compete in the market, the LICC aims to develop its industry andcontribute to society through shared operations of managing arent subrogation payment information database. In addition, wewish to thank the LICC for its cooperation in this research.

properties and an average rent of 53 594 yen, the total annual
arrears amount for the whole of Japan is approximately 68.3
billion yen. This does not include the costs to eliminate the[1]

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