Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, Vol.16, No.6, September 2020

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Relationship between School Attendance Support and Academic Performance: An Analysis of Panel Data from Adachi Ward＊1
NOGUCHI Haruko
Professor, Faculty of Political Science and Economics, Waseda University

BESSHO Shun-ichiro
Associate Professor, Faculty of Economics, The University of Tokyo / Former Chief Economist, Policy Research Institute,
Ministry of Finance

USHIJIMA Koichi
Assistant Professor, Division of Policy and Planning Sciences, Faculty of Engineering, Information and Systems, University of Tsukuba

KAWAMURA Akira
Associate Professor, Faculty of Political Science and Economics, Waseda University

TANAKA Ryuichi
Professor, Institute of Social Science, The University of Tokyo

Abstract
The aim of this paper is to perform quantitative analysis about the relationships between
receipt status of school financial support and student’s characteristics such as academic performance, obesity, home-learning conditions, everyday attitudes towards learning, and academic performance and physical capabilities. Focusing on all pupils and students attending
Adachi ward (Tokyo) public elementary schools and junior high schools, we construct panel
data by linking two surveys (“The Survey on the Physical Capabilities of Pupils and Students,” and the “Adachi Comprehensive Survey of Acquisition of Basic Academic Skills”(conducted from second year of elementary school until third year of middle school), which
was independently conducted by Adachi ward in 2009–2017) to pupil/student name registers(list of school-age children) with information about application for and receipt of school attendance support. Even having controlled for pupils’ and students’ fixed-effects, the resultsof this analysis reveal the possibility that pupils and students who are continuous beneficiaries of public assistance may be put in circumstances with difficulties to learning. We findthat, pupils and students who are not eligible for national public assistance but receive municipal school attendance support are in better conditions in terms of overall academic performance and home-learning compared to pupils and students that are continuous beneficiaries of public assistance. Regarding the relationship between academic performance andphysical capabilities, it was revealed that, having controlled for pupils’ and students’                          

＊1This paper was produced as part of the MEXT KAKENHI Grant-in-Aid for Scientific Research (B) (General) project “AnEmpirical Research on the Accumulation Mechanism of Children’s Human Capital: Lessons from Challenge of Adachi Wardin Tokyo Prefecture” (No. 16H03636).

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NOGUCHI Haruko, BESSHO Shun-ichiro, USHIJIMA Koichi, KAWAMURA Akira, TANAKA Ryuichi / Public Policy Review

fixed-effects, there is a high probability that there is a positive correlation between physicalcapabilities and academic performance, and a negative correlation with obesity.
Keywords: school financial support; academic performance; obesity; home-learning
conditions; everyday attitudes towards learning; physical capabilities.
JEL Classification: I21, J24

I.  Introduction
Adachi ward designated 2015 the “Inaugural Year of Child Poverty Countermeasures.”
Recognizing it to be important that all children acquire “survival strength” to carve out theirown futures, without being unduly influenced or controlled by the environments in which
they have been born and raised, the ward promotes concrete projects and developments built
on the three foundations of “education and learning,” “health and lifestyle,” and “building
schemes to encourage change.” Comprehensive measures to counter child poverty are being
implemented as part of this endeavor, with schools as a “platform”: (1) support for securing
academic performance and experience; (2) providing learning environments that incorporate
links with consultation systems and relevant institutions; (3) guaranteeing place to be; and(4) implementing measures focused on career support for the future.1
The aim of this paper is to focus on “education and learning” from amongst these threepillars and gain a statistical understanding of the actual conditions of children’s upbringings(academic performance and attitudes). Accordingly, we perform quantitative analysis about
the relationships between school financial support receipt status and student’s characteristics
such as academic performance, obesity, home-learning conditions and everyday attitudes towards learning. Focusing on all pupils and students attending Adachi ward public elementary schools and junior high schools, we construct panel data by linking pupil/student nameregisters (list of school-age children), information about application for and receipt of school
attendance support, and two surveys, that is, “The Survey on the Physical Capabilities of
Pupils and Students,” and the “Adachi Comprehensive Survey of Acquisition of Basic Academic Skills” (conducted from second year of elementary school until third year of middle
school), which was independently conducted by Adachi ward in 2009–2017. This study also
inspects the relation between physical capabilities and academic performance, and thereby
aims to gain a comprehensive understanding of processes in the upbringing of pupils andstudents in the stages of compulsory education, in the context of school attendance support
receipt status. One characteristic feature and contribution of this paper is its use of panel
data on individual pupils and students, which has not previously seen much use in Japan, toquantitatively clarify the relationships between school attendance support receipt status and                          Adachi ward website (https://www.city.adachi.tokyo.jp/sesaku/miraihetunaguadachipurojekuto.html) (Accessed: April 16,2018).

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Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, Vol.16, No.6, September 2020

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a variety of indicators of upbringing, whilst controlling for pupils’ and students’ fixed-effects.
The results of this analysis revealed the following points. First, regarding the relationships between school attendance support receipt status and academic performance and obesity, and home-learning conditions and everyday attitudes towards learning, even having
controlled for pupils’ and students’ fixed-effects, the results suggest that pupils and students
continuously belonging to the category of beneficiaries of (national) public assistance may
be placed in circumstances with difficulties to learning. Pupils and students receiving school
attendance support subsidies independently implemented by the local government (who are
not eligible for national public assistance but still need support) were, with statistical significance, in better condition in terms of overall academic performance and home-learning circumstances compared to pupils and students who are continuous public assistance beneficiaries. Accordingly, these measures may be offering some help for pupils and students facing
economic hardship. Lastly, regarding the relationship between academic performance andphysical capabilities, having controlled for pupils’ and students’ fixed-effects, we see a positive correlation between physical capabilities and academic performance, and observe anegative correlation between physical capabilities and obesity, but no statistically-significant
correlation is observed for school attendance support status, which is a proxy variable for
economic circumstance.
The research literature that is relevant to the study in this paper differs depending onwhether the “school attendance support receipt status” is seen as a proxy variable for household income, or as a change in income to a low-income household. If this school attendance
support receipt status is seen as a proxy variable for household income, there are countlessstudies that have investigated how household income is associated with indicators of upbringing such as academic performance. Particularly in Japan, there is a plethora of resultsof such research by educational sociologists such as Kariya (2001) and Mimizuka (2014).
Our study differs greatly from this previous research in that we use panel data to comprehensively analyze relations to obesity and physical capabilities too, for instance, whilst controlling for children’ fixed effects.
One example of analysis that considers relations between receipt of free or reduced-pricelunches as a proxy variable for household income, academic performance, obesity
home-learning conditions and everyday attitudes towards learning, is presented by Morrissey, Hutchison, and Winsler (2014). Their paper uses data concerning children from theirtime in kindergarten to fourth year of elementary school in Florida, in the United States, toexamine the relations between information about measures for providing children from
low-income households with free or reduced-price lunches, school attendance rates, and academic performance. The results reveal that the attendance rates and academic performanceare relatively low for children receiving free or reduced-price lunches compared with children who do not receive free or reduced-price lunches. Whilst this study does analyze therelation between various indicators of upbringing and household income, our research differs in that we also conduct more comprehensive analysis of home-learning conditions and4

NOGUCHI Haruko, BESSHO Shun-ichiro, USHIJIMA Koichi, KAWAMURA Akira, TANAKA Ryuichi / Public Policy Review

everyday attitudes towards learning and, furthermore, analyze relationships to physical capabilities.
Studies from outside of Japan that examine the effects exerted on household consumption and assets by changes in income and provision of subsidies for low-income households
include Fishback and Kantor (1995), Hubbard, Skinner, and Zeldes (1995), Gruber (1997),(2000), Engen and Gruber (2001), and Gruber and Yelowitz (1999). Research that focuses
specifically on relations with development in terms of childrens’ academic performance,
physical capabilities, and so forth, includes Currie and Moretti (2008), and Hoynes andSchanzenbach (2009), for instance, which analyze results of Food Stamp Programs. Even inglobal terms, however, there are few studies that conduct comprehensive analysis of a variety of indicators, having considered receipt of school attendance support, such as that examined in the present paper, as signifying transfers to low-income households.
The structure of the present paper is as follows. Section II provides a simple descriptionof the school attendance support system. Section III describes the data used in analysis. Section IV introduces the regression models used in analysis, and subsequently Section V explains the analysis results. Section VI considers the implications and limitations of the paper, and provides a conclusion.

II.   School attendance support
Article 19 of the School Education Law stipulates that “municipalities shall grant necessary support to guardians of school-age pupils and students recognized as facing difficultyattending school due to economic reasons,” and thus school attendance support is implemented by municipalities. The recipients of this support are: “public assistance beneficiaries” as prescribed in the Public Assistance Act; and “school attendance support beneficiaries,” who are recognized by the municipal board of education to be facing a degree ofhardship equivalent to public assistance beneficiaries. With Public Assistance, half of theamount needed for providing support to public assistance beneficiaries is covered by theJapanese national government using the Central Government Subsidy for Public Assistancefor pupils and students requiring public assistance. Meanwhile, state subsidies for aiding
school attendance support beneficiaries were abolished from 2005 following the Trinity Reform Package; local fiscal measures have been put in place, and thus this support is independently implemented by each municipality. Matters subject to this aid include lunch expenses, commuting expenses, off-campus activity expenses, medical expenses, and expenses
for any items necessary for school attendance.
Table 1-1 indicates the 2016 school attendance support certification criteria in Adachi
ward in and neighboring wards. The public assistance and school attendance support receipt
rate for 2015 in Adachi ward is 35–40%, which is highest not only amongst neighboring
wards, but across all of the 23 wards in Tokyo. The condition for certification for receipt ofschool attendance support is any of the following: “suspension or cessation of support basedon the Public Assistance Act,” “provision of childcare allowance,” and “a fixed coefficient5

Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, Vol.16, No.6, September 2020

Table 1-1. School attendance support certification criteria for Adachi Ward and neighboring wards (2016)
School attendance support certification criteria

Previous fiscal year 419

○

○

○

○

○
○
○
○

○
○
○

○
○
○
○

○
○

(9) Other

1.2 Tax basis

○

○
○
○
○

(8) Lectures conducted for guardians○○○(7) Lectures conducted for teaching staff○(6) Featured in school attendance guidancematerials○○(5) Written notice to schools○○

1.2 Other
1.2 Other

1.1 Tax basis○(4) Featured in local government publicity
materials○○(3) Featured on Board of Education website○○○(2) School attendance support system
documents distributed at schools at timeof enrolment

○

○
○
○
○

Period for baseamountFiscal year 3 years
399
prior
Previous fiscal year 347
Other
400

Type, e.g. tax basis(1) Documents distributed at schools
each year at time of advancement to next
grade

○

Under 30%
Under 35%
Under 30%
Under 30%Grounds for basis

Target figure amount (annual)

Under 40%

Katsushika Ward
Sumida Ward
Arakawa Ward
Kita Ward

Methods for notifying about school attendance support
system (multiple answers allowed)
For (7): Coefficient (multiplication rate), grounds for Child poverty
basis, and target figure amountindicators
Coefficient (multiplication rate)

Adachi Ward

(8) Other(7) A fixed coefficient multiplied by thestandard public assistance amount used tomeasure the required amount for
special-assistance education attendance funds,
or, the standard amount for public assistance(6) Provision of childcare allowance(5) National Health Insurance Act payment
reduction, exemption, or postponed settlement(4) National pension insurance payment
exemption(3) Local inhabitant tax reduction(2) Local inhabitant tax exemption(1) Suspension or cessation of support basedon the Public Assistance Act

Public assistance or school attendance support receipt
rate in 2015

Municipality name○multiplied by the standard public assistance amount used to measure the required amountfor special-assistance education attendance funds, or, the standard amount for public assistance.” This “standard public assistance amount times a certain coefficient” is “1.1 times thestandard public assistance amount”; an applicant is certified for school attendance support if
their tax basis is smaller than this threshold, and that standard is 3,990,000 yen annually.
The school attendance support certification criteria include no conditions such as the “local
inhabitant tax reduction or exemption” used by Sumida ward, and the standards are also
lower than areas such as Sumida ward and Kita ward. Adachi ward’s certification examination application procedures happen following the start of the new fiscal year in April, andcertification itself happens in June–July. Note that the public assistance and school attendance support receipt rate for 2016 is 32.3% for the whole of Adachi ward (29.4% for elementary schools, 38.7% for middle schools), and although this rate has tended to decrease inrecent years, it still greatly surpasses Japan’s national average of 15.4% and Greater Tokyo’s
average of 20.5%.
As Table 1-2 indicates, in Adachi ward, guardians of elementary and middle school pupils and students receive assistance for elementary school pupils for: expenses for schoolsupplies (fixed amount), expenses for school supplies for pupils and students entering new
schools (fixed amount), commuting expenses (actual expenses), off-campus activities (varies
depending on whether or not overnight accommodation is involved; fixed amount), andschool club expenses. Assistance is also provided for middle school students for sports
equipment expenses (up to a certain limit) and school trip expenses (fixed amount), in addition to the matters above. Note that since lunch and school trip expenses are paid for via deposit into the school principal’s account, these matters are provided in kind. Insofar as Table
1-2 indicates, the amounts of assistance provided are roughly the same levels as neighboring
wards, and other 23 wards across Tokyo.
In this paper, “public assistance” refers to persons requiring public assistance as stipulated in Article (6), Paragraph (2) of the Public Assistance Act, and “school attendance support” refers to persons recognized by the municipal board of education to be facing degrees

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Table 1-2. Elementary and middle school attendance support certification standards for Adachi Ward and neighboring wards (2016)
Municipality Elementary school attendance support amount items (amounts provided annually per person)
nameExpenses for school
School supplies

supplies for pupils andstudents entering new schools

School club expenses
Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up to alimit,’ upper-limit amount)

Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’ upper-limit
amount)Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up to alimit,’ upper-limit amount)

3,810

3,810

Other

1,510

Other

7,400
(forestcamp
school)8,370(seaside
school)7,400(forestcamp
school)8,370(seaside
school)Fixedamount

240

240

1,388

Upper-limit 8,370
amount7,810

Upper-limit 240
amount238

5,365(fourth/fifth
years)

Fixedamount

240

Fixed
1,920
amount

1,920

1,400
(first/second
years) 2,100
Fixed(third/fourthamountyears)
3,000 (fifth/
sixth years)

1,400(first/second
years) 2,100(third/fourthyears)
3,000 (fifth/
sixth years)

Actualexpens- 1,510
es

SumidaWard

15,690 (firstyear);
Fixed
18,880amount(second tosixth years);

15,690 (firstyear);
Fixed
18,88023,890amount(second tosixth years);

23,890

Arakawa
Ward

Fixed
18,888amount18,888

Fixed
23,890amount23,890

Actualexpens- 10,285
es

10,285Upper-limit 2,120
amountKita Ward

18,88018,880(second to(second tosixth years) sixth years)
Fixed
Fixed
(including(including
23,890amountamountexpenses for expenses forcommuting commuting
supplies)
supplies)

23,890

Actualexpens- 5,418
es

5,418

Fixed
3,400 (fifth/ 3,400 (fifth/ Fixedamount sixth years) sixth years) amount

5,365(fourth/fifth
years)

Form of payment

Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’ upper-limit
amount)FixedamountForm of payment

5,660(sixthyear);
4,650(special
education
class)

Off-campus activities(with overnight stay)
Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up to alimit,’ upper-limit amount)

8,489

5,660
(sixthyear);
Fixed
4650
amount(special
education
class)

Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’ upper-limit
amount)12,800Form of payment

Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up to alimit,’ upper-limit amount)

22,800

Actualexpens- 8,489
esAmount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’ upper-limit
amount)Actualexpens- 12,800
es

Form of payment

23,890Off-campus activities(without overnight stay)

School trip expenses
Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up to alimit,’ upper-limit amount)

Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’ upper-limit
amount)Form of payment

Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up to alimit,’ upper-limit amount)

Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’ upper-limit
amount)Form of provision

Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up to alimit,’ upper-limit amount)

Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’ upper-limit
amount)Form of provision

19,12019,120(including(including
expenses for expenses forcommuting commuting
Fixed
Fixed
Adachi Wardsupplies,
supplies,
23,890amountamountextracurricu- extracurricular/clublar/clubactivity
activity
supplies)
supplies)
15,400 (first 15,400 (firstyear); 18,450 year); 18,450(second/third (second/third
Fixed
Katsushika Fixed
years);
years)
22,800amountWardamount18,66018,660(fourth to(fourth tosixth years) sixth years)

Commuting expenses

240

Note: School attendance support in these areas does not cover single-item commuting supplies expenses, student
council fees, PTA fees, home-learning expenses (e.g., cost of purchasing textbooks)
Municipal- Middle school attendance support amount items (amounts provided annually per person)
ity name
Expenses for school supSchool supplies
plies for pupils and students Commuting expenses
entering new schools

26,860

Actualexpens- 47,800
es

47,800

Fixed
Fixed
57,290 57,290
3,090
amountamountFixed
4,270
amount

4,270

Fixed
26,300amount26,300

Actualexpens- 35,637
es

35,637600 (first
600 (firstyear); 1,600 year); 1,600(second(second
Fixed
Fixed
Fixed
60,000 60,000
year);
year);
3,200
amountamountamount3,400 (third 3,400 (thirdyear);
year);
1,000(night) 1,000(night)

3,200

Fixed
26,860amount26,860Fixed
26,860amount26,860

Actualexpens- 39,930
es

Fixed
26,860amount26,860

Actualexpens- 28,879
es

3,090

UpActual
per-limit 69,750 57,444
2,380
expenses
amount2,380

39,930

UpUpper-limit 69,750 67,327 per-limit 3,090
amountamount2,991

28,879UpFixed
5,200 (third 5,200 (thirdper-limit 61,000 61,000
amount year);year);
amountForm of provision

Fixed
26,860amountSchool supplies
Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up
to a limit,’ upper-limit amount)
Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’
upper-limit amount)

Form of provision

Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up
to a limit,’ upper-limit amount)
Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’
upper-limit amount)

Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up
to a limit,’ upper-limit amount)

Form of provision

Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’
upper-limit amount)

Form of provision

3,951

Off-campus activities Off-campus activities (with overSchool club expenses(without overnight stay) night stay)
Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up
to a limit,’ upper-limit amount)
Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’
upper-limit amount)

34,41034,410(second/third (second/thirdyears)
years)
UpFixedKita Ward(including(including
per-limit 7,860
amountexpenses for expenses for amountcommuting commuting
supplies)
supplies)

Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up
to a limit,’ upper-limit amount)

34,416

Form of provision

Fixed
34,416amountAmount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’
upper-limit amount)

Arakawa
Ward

4,511

Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up
to a limit,’ upper-limit amount)

30,450 (first 30,450 (first
UpFixed year); 34,410 year); 34,410
per-limit 7,860
amount (second/third (second/thirdamountyears)
years)

Form of provision

SumidaWard

Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’
upper-limit amount)

Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up
to a limit,’ upper-limit amount)

Form of provision

Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’
upper-limit amount)

Average amount provided (Note: If ‘actual
expenses,’ actual expenses amount; if ‘up
to a limit,’ upper-limit amount)

Amount (Note: If ‘actual expenses,’ actual
expenses amount; if ‘up to a limit,’
upper-limit amount)

Form of provision

35,64035,6407,510(including(including(upperexpenses for expenses forlimit forcommuting commuting UpAdachi
Fixed
judo)
supplies,
supplies,
per-limit
3,820
Ward
amount
51,940extracurricu- extracurricu- amount(upperlar/clublar/club
limit foractivity
activity
kendo)
supplies)
supplies)
7,440(upper30,40030,400limit for(first year); (first year); UpKatsushika Fixedjudo)
34,30034,300per-limit
4,094
Ward
amount50,400(second/third (second/third amount(upperyears)
years)
limit forkendo)

School trip expenses

Other

10,290 10,290(forest (forest
camp camp
Fixed
Other
school) school)
1,230
amount11,840 11,840(seaside (seaside
school) school)
UpUpper-limit 7,250 6,322 per-limit 1,230
amountamount

1,230

1,105

Note: School attendance support in these areas does not cover single-item commuting supplies expenses, student
council fees, PTA fees, home-learning expenses (e.g., cost of purchasing textbooks)

Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, Vol.16, No.6, September 20207of hardship equivalent to public assistance beneficiaries as stipulated in Article (6), Paragraph (2) of the Public Assistance Act. In some cases, a person does apply for school attendance support but is not certified; persons who applied but were not eligible to receive
school attendance support expenses are referred to as “rejected applicants.”

III.   Data
This paper focuses on all pupils and students attending Adachi ward public elementary
schools and junior high schools, and uses panel data built by linking: (1) data from the “Adachi Comprehensive Survey of Acquisition of Basic Academic Skills” (hereinafter: “Adachi
Basic Academic Skills Survey”; subjects from second year of elementary school to thirdyear of middle school), which was independently conducted by Adachi ward in 2009–2017;(2) pupil/student name registers (hereinafter: “list of school-age children”); (3) data regarding application for and receipt of school attendance support; and (4) “The Survey on the
Physical Capabilities of Pupils and Students” (hereinafter: “Physical Capabilities Survey”).
Note, however, that the “Physical Capabilities Survey” is not yet completely linked; this paper, therefore, uses only survey results from 2015–2016. The number of observed values foreach year is approximately 37,000–39,000. Please refer to Bessho et al. (2020) included inthis special issue for further details of the procedures involved in creating the data.
The data in this paper includes the following information. First, the Adachi Basic Academic Skills Survey includes the results of academic performance tests and attitude surveys(questionnaires) that were conducted on pupils and students. The academic performance test
includes results in Japanese language arts and mathematics for elementary school pupils intheir second year and above, and results in Japanese language arts, mathematics and English
for middle school students (English results are included only for second- and third-year
middle school students). The attitude survey acquires responses from pupils and students regarding home-learning conditions, everyday attitudes towards learning, and so forth. For instance, the Adachi ward Board of Education places emphasis on “haya-ne, haya-oki, asa-gohan” (literally, “early to bed, early to rise, breakfast,” a motto indicating three important
aspects of a child’s daily life), and in order to acquire information about the circumstancesof pupils and students regarding these elements, the survey poses questions on a range ofdozens of items, such as “Do you eat breakfast every day?” and “Do you normally live in a
regular/disciplined fashion?” Second, school attendance support status is differentiated as
mentioned in the previous section, i.e. between: “public assistance” beneficiaries, referring
to persons as stipulated in Article (6), Paragraph (2) of the Public Assistance Act; “school
attendance support” beneficiaries, referring to persons recognized by the municipal board ofeducation to be facing degrees of hardship equivalent to public assistance beneficiaries as
stipulated in Article (6), Paragraph (2) of the Public Assistance Act; and “rejected applicants,” referring to persons who applied for school attendance support but were not eligible
to receive expenses. Third, the “Physical Capabilities Survey” includes: height and bodyweight, measurement values for grip strength, sit-ups, toe-touches, side-steps, 20m shuttle

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run (beep test), 50m sprint, standing long-jump, long-distance run, and a total physical capability score calculated from these individual items.
The children who could be tracked over the longest time period from the data in this paper are those who were in the second year of elementary school in 2009 and 2010; Figure 1
shows the results of tracking the school attendance support receipt status receipt status ofthese children until their third year of middle school. This reveals that the school attendance
support receipt rate is around 33–35% and the public assistance receipt rate around 3–4%
Figure 1. Trends in school attendance support status for 2009 and 2010 Elementary school, second year cohort
2009 Elementary school, second year cohort

Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, Vol.16, No.6, September 202092010 Elementary school, second year cohort

for any of the cohorts; compared with the national average school attendance support receipt
rate (around 13–14%) and public assistance receipt rate (around 1.5%) for the same periods,
the aid receipt rate in Adachi ward is substantially higher. Figure 1 also shows that theschool attendance support receipt rate tends to discontinuously increase due to omission
from the cohort of pupils that move into private education when the cohort advances to middle school.

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IV.  Estimation method
IV-1.  School attendance support status and academic performance and obesity,and home-learning conditions and everyday attitudes towards learningThis paper uses fixed-effects models and random-effects models to quantitatively investigate the relationships between school attendance support status and academic performance,
obesity, home-learning conditions, and everyday attitudes towards learning. The estimation
model is as follows.
iyti = α + βjk sjkt
+ ηgradeti + θyear + μi + νit (1)
In equation (1), the dependent variable y ti indicates the acadeic performance, obesity,
home-learning conditions, everyday attitudes towards learning of pupil or student i at time t.
Point scores for Japanese, arithmetic/mathematics and English have been standardized on
the basis of the average values and standard deviations for each year and grade to have an
average of 50 and a standard deviation of 10, and are used as dependent variables for academic performance. For obesity, since the survey measures body weight and height, we create a “Rohrer’s Index (body weight (kg) ÷ height (cm)^3×10^7)” to indicate the obesity levels of pupils and students of middle-school age and below. A Rohrer’s Index of under 100 is
defined as “underweight,” from 100 to under 115 is defined as “slightly underweight,” from
115 to under 145 as “normal,” from 145 to under 160 as “slightly obese,” and 160 and above
as “obese.” Here we make a Rohrer’s Index of 160 and above into an obesity dummy variTable 1. Trends in school attendance support status
sjk

School attendance support status at current time (k)Rejected
applicantSchool attendance support

Publicassistances00
s01
136,551 (92.64) 4,771 (3.24)

s02
5,706 (3.87)

s03
371 (0.25)

Non-applicant
Non-applicant

Schools11
s12
s10
attendance Rejected applicant
5,106 (36.63) 6,722 (48.22) 2,095 (15.03)
supportstatus at
s21
s22
School attendances20
previous
2,841 (3.30) 5,403 (6.28) 77,226 (89.78)
supporttime (j)Public assistances30
328 (4.29)

s31
0 (0.0)s32
499 (6.53)

s13
18 (0.13)s23
550 (0.64)
s33
6,814 (89.18)

Note: The numerical values is the number of observed values; in parenthesis is the ratio (%) this is of child numbers at the previous time. Pearson chi2(9) = 4.4e+05 (Pr = 0.000)

Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, Vol.16, No.6, September 202011

able, and of under 100 into an underweight dummy variable, which are used as dependent
variables. For home-learning conditions and everyday attitudes towards learning, we use,from the results of the attitude survey accompanying the Adachi Basic Academic Skills Survey: a response of “attends private tuition” as 1 (otherwise, 0); a response of “there is no
one at home to help with study” as 1 (otherwise, 0); a response of “checks unfamiliar words
in a Japanese dictionary (including eletronic dictionaries)” or “sometimes checks [...]” as 1
(otherwise, 0); and a response of “thinks of alternative solving methods in arithmetic/mathematics problems” or “usually thinks of [...]” as 1 (otherwise, 0). Regression analysis is performed individually on the above 9 dependent variables in equation (1).
i
Next, for the explanatory variables: sjkt
indicates change in school attendance support
status (“non-applicant,” “rejected applicant,” “school attendance support”, “public assistance”) from the previous time (j) through to the current time (k) for pupil or student i. As
shown in the Table below, “non-applicant” is expressed as 0, “rejected applicant” as 1,“school attendance support” as 2, and “public assistance” as 3. For instance: s00 indicates thestatus was previously and is still now “non-applicant,” s01 indicates the status was previously “non-applicant” but is now “applied but rejected,” s02 indicates the status was previously“non-applicant” but is now “school attendance support,” and s03 indicates the status was previously “non-applicant” but is now “public assistance.” In equation (1), s33 is treated as anomitted variable, and s01−s32 are all added as binary variables. Note that, owing to the system
requirements for school attendance support, as detailed previously, no child changes frompreviously ( j) being “public assistance” to currently (k) being “rejected applicant,” and thus
s31 should be zero for all pupils and students. In fact, the number of observed values for s31=1 was 0, and thus s31 is not included as an explanatory variable. Grade and year dummies
have also been added.
Here, we take a 1-year lag, and look at the influence of changes in school attendance
support status from the previous time (j) until the recent time (k). The Adachi Basic Academic Skills Survey is conducted each year in April, at the start of the fiscal year. School attendance support applications are submitted from each household in April, at the start of the
fiscal year and, following examination, it is decided in July whether or not assistance will be
provided. The status indicated in the school attendance support data refers to the time at theend of the fiscal year. If the explained variables are the results of the Adachi Basic Academic
Skills Survey conducted in April 2016, for instance, then school attendance support changes
from July 2015 to July 2016—i.e., when decisions are made regarding the provision/
non-provision of school attendance support—will be used as the explanatory variables.
Since school attendance support status decided in July 2016 reflects household circumstances in April 2016, the analysis in this paper will estimate the effects exerted on children’s academic performance, obesity, and home-learning conditions by changes in school attendance
support status at the time tests were conducted.
In equation (1), α, βjk , γ, η, θ indicate estimated coefficients, and the term μi represents
the children’s unobservable (unobserved) attributes that do not change over time, i.e., their
fixed effects. Additionally, νit is a usual error term, for which νit~i. i. d. N (0, σ2ν) is assumed.

12

NOGUCHI Haruko, BESSHO Shun-ichiro, USHIJIMA Koichi, KAWAMURA Akira, TANAKA Ryuichi / Public Policy Review

This paper conducts estimations using fixed-effects models and random-effects models,and performs an F-test and a Durbin-Wu-Hausman test in order to select between the models. First, the F-test verifies the statistical significance of any fixed effects. Next, if the null
hypothesis, in which there is no correlation between random-effects and explanatory variable xkit-1 is dismissed in the Durbin-Wu-Hausman test, then a fixed-effects model is preferable to a random-effects model. Since fixed-effects models were chosen in all instances inthis paper, only the fixed-effects model results will be discussed hereinafter.

IV-2.   Physical capabilities and academic performanceThis paper also uses a fixed-effects model and a random-effects model to conduct quantitative investigation into the relation between physical capabilities and academic performance. The estimation model is as follows.
zti=δ+ζjtestscorejti +λoverweightti+ρathleticclubti+σk skti +πgradeti+τ year+ψi+εit(2)
In equation (2), zti indicates the total physical capability score at time t for child i. Notably, these measurement values have all been nationally standardized according to Tokyo
metropolitan government, and therefore can also be compared in time series.
For the explanatory variables: in analysis of the whole sample, testscorejti uses the standardized scores for Japanese and arithmetic/mathematics ( j=1, 2). The standardized scoresfor English have not been included because we only have data for the second and third yearsof middle school, resulting in significantly lower numbers of observed values. overweightti isa variable that indicates tendency towards obesity using a Rohrer’s Index, which calculatedon the basis of height and body weight: the variable takes a value of 1 if the Index is at least
160, and 0 otherwise. athleticclubti is a dummy variable taking a value of 1 if a child belongs
to a sports club, and a value of 0 if otherwise. The previous year’s school attendance support
status is included as skti , with “non-applicant” as an omitted variable (k =1, 2, 3). Grade andyear dummies have also been added. δ, ζj, λ, ρ, βk , σ, π, τ indicate estimated coefficients, andthe term ψi represents the children’s unobservable (unobserved) attributes that do not changeover time, i.e., their fixed effects. Additionally, εit is a general error term, for which εit~i. i. d.
N (0, σ2ε) is assumed. In the same manner as with academic performance, an F-test and a
Durbin-Wu-Hausman test were performed, resulting in fixed-effects being selected; the discussion in this paper therefore focuses on fixed-effects.

V.  Estimation results
V-1.  Summary statistics
The average values and standard deviations of the results of the Adachi Basic Academic
Skills Survey and the Physical Capabilities Survey are shown by school attendance support
receipt status in Table 2-1 and Table 3-1 for, respectively, elementary schoolers and middle
schoolers. These Tables reveal that in all subjects—Japanese, arithmetic/mathematics, and13

Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, Vol.16, No.6, September 2020

English—the children who have not applied for school attendance support have the highest
standardized scores, followed by rejected applicants, school attendance support, and thenpublic assistance, who each have successively lower standardized scores. For reference, thebox-and-whisker plots in Figures 2-1 to 2-3 show the variation in standardized scores foreach subject by school attendance support status and by school year. In the box-and-whisker
plots, the top line of each box indicates the upper quartile (75%), the middle line indicatesthe median value, the bottom line of each box indicates the lower quartile (25%), and thetips of the whiskers indicate the maximum and minimum values. These figures show that in
all academic subjects and all school years, the median standardized scores for pupils andstudents who have not applied for school attendance support is over 50; by contrast, the median standardized scores for public assistance beneficiary pupils and students is under 50.
Moreover, the larger difference between the standardized scores of the upper 25% and thelower 25% indicates that there is great variation amongst such pupils and students.
Table 2-1. Summary statistics for academic performance, physical attributes and physical capabilities according to school attendance support receipt status (Elementary school)
1. Academic performance
Japanese standardized score
Arithmetic standardized score

Non-applicant
Obs
Mean Std. Dev.

School attendance support receipt status
Rejected applicant
School attendance support
Obs
Mean Std. Dev.
Obs
Mean Std. Dev.

Public assistanceObs
Mean Std. Dev.

95,997
95,997

51.56
51.57

(9.25)(9.16)

7,817
7,817

49.71
50.03

(9.72)(9.69)

47,92847,928

47.90
47.91

(10.36)(10.44)

4,004
4,004

43.66
42.82

(11.52)(11.94)

2. Physical traits and capabilities
Body weight (kg)Body weight: standardized score
Height (cm)Height: standardized score
Rohrer's Index: Body weight (kg) ÷ Height (cm)^3×10^7→ Underweight: Rohrer's Index of under 100→ Slightly underweight: Rohrer's Index of 100–115→ Normal: Rohrer's Index of 115–145→ Slightly obese: Rohrer's Index of 145–160→ Obese: Rohrer's Index of 160 or higher
Grip strength (national standardized score)Sit-ups (national standardized score)Toe-touches (national standardized score)
Side-steps (national standardized score)
20m shuttle run (national standardized score)
50m sprint (national standardized score)Standing long-jump (national standardized score)
Total physical abilities score (national standardized score)

23,662
23,662
23,72023,72023,63923,63923,63923,63923,63923,63923,732
23,65923,72923,69023,596
23,677
23,68823,34332.63
49.78
136.9950.15
125.50   0.02   0.26   0.60   0.07   0.04
48.53
50.22
50.28
48.90
48.48
49.14
48.04
48.07

(7.89)(9.60)(9.24)(9.91)(17.05)(0.13)(0.44)(0.49)(0.26)(0.20)(10.80)(9.98)(10.93)(10.38)(9.67)(17.83)(10.73)(10.81)

2,131
2,131
2,137
2,137
2,128
2,128
2,128
2,128
2,128
2,128
2,140
2,135
2,140
2,135
2,124
2,132
2,136
2,103

32.87
49.53
137.2949.62
125.54   0.01   0.26   0.61   0.07   0.05
49.39
50.87
50.85
48.93
49.19
48.90
48.44
49.05

(8.15)(9.92)(9.37)(10.04)(17.39)(0.12)(0.44)(0.49)(0.25)(0.21)(11.32)(10.24)(10.92)(10.55)(9.96)(36.38)(10.50)(10.76)

10,716
10,716
10,754
10,754
10,695
10,695
10,695
10,695
10,695
10,695
10,786
10,748
10,788
10,762
10,702
10,753
10,764
10,57533.21
50.31
137.0649.71
127.38   0.02   0.24   0.60   0.08   0.06
49.08
49.93
50.30
47.73
47.43
48.06
47.43
47.43

(8.51)(10.55)(9.32)(10.03)(18.72)(0.13)(0.42)(0.49)(0.27)(0.24)(11.04)(9.89)(11.01)(10.50)(9.64)(26.30)(10.80)(10.49)

888
888
896
896
887
887
887
887
887
887
898
889
893
890
881
882
889
863

34.47
52.27
137.0149.83
131.86   0.01   0.17   0.59   0.14   0.09
49.29
48.03
49.04
45.70
45.32
45.99
45.38
44.95

(9.51)(11.81)(9.84)(10.75)(20.13)(0.11)(0.37)(0.49)(0.34)(0.29)(11.41)(10.34)(11.42)(10.36)(9.14)(13.72)(11.27)(10.77)

Variable

Table 3-1. Summary statistics for academic performance, physical attributes and physical capabilities according to school attendance support receipt status (Middle school)
1. Academic performance
Japanese standardized score
Arithmetic standardized score
English standardized score

Non-applicant
Obs
Mean Std. Dev.

School attendance support receipt status
Rejected applicant
School attendance support
Obs
Mean Std. Dev.
Obs
Mean Std. Dev.

Public assistanceObs
Mean Std. Dev.

51,40251,40235,398

51.70
52.02
52.07

(9.40)(9.41)(9.63)

6,124
6,124
4,313

49.80
49.99
49.61

(9.68)(9.58)(9.63)

38,092
38,092
26,618

48.62
48.31
48.08

(10.04)(9.90)(9.81)

3,637
3,637
2,537

44.98
43.54
44.24

(10.77)(10.18)(9.64)

2. Physical traits and capabilities
Body weight (kg)Body weight: standardized score
Height (cm)Height: standardized score
Rohrer's Index: Body weight (kg) ÷ Height (cm)^3×10^7→ Underweight: Rohrer's Index of under 100→ Slightly underweight: Rohrer's Index of 100–115→ Normal: Rohrer's Index of 115–145→ Slightly obese: Rohrer's Index of 145–160→ Obese: Rohrer's Index of 160 or higher
Grip strength (national standardized score)Sit-ups (national standardized score)Toe-touches (national standardized score)
Side-steps (national standardized score)
20m shuttle run (national standardized score)
50m sprint (national standardized score)Standing long-jump (national standardized score)
Total physical abilities score (national standardized score)Long-distance run (national standardized score)

12,87812,878
12,84012,84012,492
12,492
12,492
12,492
12,492
12,492
13,356
13,311
13,41813,317
5,160
13,056
13,35012,211
10,65047.54
49.86
156.81
50.15
122.19   0.05   0.33   0.52   0.07   0.03
47.75
48.14
47.17
46.84
47.06
46.27
46.21
44.89
44.22

(8.61)(10.22)(7.58)(9.89)(16.90)(0.22)(0.47)(0.50)(0.25)(0.17)(10.29)(10.37)(10.27)(11.10)(10.24)(23.45)(11.14)(10.30)(13.52)

1,705
1,705
1,711
1,711
1,664
1,664
1,664
1,664
1,664
1,664
1,771
1,772
1,782
1,768
  735
1,713
1,776
1,621
1,425

47.90
50.08
157.1050.18
122.88   0.04   0.33   0.53   0.07   0.04
47.96
47.98
46.87
46.63
46.91
45.78
45.91
44.91
44.10

(8.40)(10.15)(7.65)(9.94)(17.10)(0.20)(0.47)(0.50)(0.25)(0.19)(10.17)(10.77)(10.10)(11.50)(9.83)(30.95)(10.83)(10.33)(13.88)

8,701
8,701
8,826
8,826
8,520
8,520
8,520
8,520
8,520
8,520
9,087
9,060
9,141
9,066
3,521
8,893
9,075
8,228
7,142

47.69
49.95
156.7049.79
123.45   0.04   0.31   0.53   0.07   0.04
47.45
47.30
46.56
45.65
45.95
44.95
44.90
43.80
42.68

(8.44)(10.27)(7.48)(10.08)(17.62)(0.21)(0.46)(0.50)(0.26)(0.19)(10.37)(10.61)(10.11)(11.41)(10.26)(33.39)(11.55)(10.34)(14.76)

  797
  797
  815
  815
  778
  778
  778
  778
  778
  778
  826
  831
  835
  823
  316
  812
  825
  724
  639

49.02
51.92
156.2749.48
128.62   0.03   0.24   0.53   0.13   0.07
48.70
46.24
46.12
43.59
43.16
43.54
43.71
42.66
39.21

(9.00)(11.28)(7.53)(10.30)(22.96)(0.17)(0.43)(0.50)(0.33)(0.26)(11.11)(11.26)(10.42)(12.15)(10.20)(13.14)(11.51)(10.71)(15.93)

Variable

14

NOGUCHI Haruko, BESSHO Shun-ichiro, USHIJIMA Koichi, KAWAMURA Akira, TANAKA Ryuichi / Public Policy Review

With regard to variables other than academic performance: the proportion of children
deemed obese on the basis of the Rohrer’s Index in elementary schools is 4% in the groupthat has not applied for school attendance support, yet tends to be higher at 9% amongst
public assistance beneficiary pupils; in middle schools, too, the proportion is 3% in thegroup that has not applied for school attendance support, yet tends to be higher at 7%
amongst public assistance beneficiary students. Furthermore, the results display low indicators for public assistance beneficiary pupils and students in all measures of physical capabilities except grip strength.
Attitude survey results are shown by school attendance support receipt status for elementary- and middle-schoolers in Table 2-2 and Table 3-2, respectively. Across all school years,
private tuition attendance rates are the highest for the group that has not applied for school
attendance support, followed by successively lower rates for pupils and students that were
rejected applicants for school attendance support, then school attendance support pupils andstudents, and then public assistance pupils and students, thus showing the same trends as academic performance. Furthermore, it is clear that, in general, higher ratios of pupils and students from school attendance support and public assistance beneficiary households faceconcerns about home-learning. The groups that have not applied for school attendance support and households that were rejected applicants for school attendance support have better
attitudes towards learning—considering, for instance, whether a child: does homework
properly; continually repeats failed problems over and over again until they understandthem; consolidates material learnt in class in a clear manner appropriate for themselves; isable to proactively tackle even difficult matters; checks unfamiliar words in a Japanese dictionary or kanji character dictionary; and thinks of alternative solving methods in mathematics problems.
Lastly, we look at lifestyle habits—e.g., whether a child: eats breakfast every day; has aregular daily routine such as sleeping early and rising early (haya-ne haya-oki); studies forat least two hours on weekdays; usually plays videogames for at least one hour per day;
Table 2-2. Basic statistics for attributes and attitude survey results according to school attendance support receipt status (Elementary school)
Variable
3. Attributes and attitudes survey results
Consolidates material learnt in class in clear, personal manner: "very true" or "somewhat true"
Can proactively tackle even difficult matters: "very true" or "somewhat true""Checks" or "sometimes checks" unfamiliar words in a Japanese dictionary (including electronic dictionaries)"Thinks" or "usually thinks" of alternative solving methods for solved arithmetic/mathematics problems
FemaleGoing to school is "enjoyable" or "quite enjoyable"
School study/classes are "enjoyable" or "quite enjoyable"
Attends private tuition
Home-learning: doesn't know what or how to study
Home-learning: has no place to study
Home-learning: no one to help with study
Does homework properly: "very true" or "somewhat true""Definitely eats" or "mostly eats" breakfast every day
Brushes teeth morning and night: "very true" or "somewhat true"
Regular daily life, e.g. early to bed & early to rise: "very true" or "somewhat true"
Sleeps for at least eight hours during normal school time
Studies for at least one hour on weekdays
Usually plays videogames for at least 1.5 hours per day
Does not read a single book in a monthHas dreams and goals for adulthood: "very true" or "somewhat true"
Sees positive parts to self: "very true" or "somewhat true"
Proactively participates in local projects: "very true" or "somewhat true"
Member of a sports teamObs

Non-applicant
Mean Std. Dev.

53,307
63,14365,53538,31991,353
95,53095,65589,364
83,19883,19883,19865,13895,697
95,52371,00682,564
71,262
95,72095,75980,75936,252
71,88823,664

0.69
0.80
0.77
0.69
0.49
0.89
0.87
0.46
0.11
0.01
0.03
0.95
0.98
0.97
0.78
0.85
0.52
0.30
0.19
0.89
0.74
0.60
0.63

(0.46)(0.40)(0.42)(0.46)(0.50)(0.32)(0.33)(0.50)(0.31)(0.11)(0.17)(0.21)(0.15)(0.17)(0.41)(0.36)(0.50)(0.46)(0.39)(0.31)(0.44)(0.49)(0.48)

School attendance support receipt status
Rejected applicant
School attendance support
Obs
Mean Std. Dev.
Obs
Mean Std. Dev.

Public assistanceObs
Mean Std. Dev.

4,278
5,154
5,958
3,729
7,686
7,791
7,797
7,322
6,798
6,798
6,798
4,980
7,795
7,775
5,526
6,750
6,517
7,787
7,797
6,780
3,282
5,716
2,135

2,471
2,555
2,645
1,664
3,920
3,968
3,974
3,739
3,522
3,522
3,522
2,891
3,985
3,973
3,121
3,475
2,915
3,988
3,985
3,410
1,287
2,892
890

0.66
0.80
0.74
0.66
0.49
0.88
0.86
0.35
0.13
0.01
0.03
0.95
0.97
0.97
0.78
0.85
0.45
0.35
0.22
0.90
0.71
0.60
0.65

(0.47)(0.40)(0.44)(0.47)(0.50)(0.33)(0.35)(0.48)(0.33)(0.11)(0.18)(0.22)(0.18)(0.17)(0.42)(0.35)(0.50)(0.48)(0.42)(0.31)(0.45)(0.49)(0.48)

28,882
31,16331,407
19,276
46,96447,62347,73144,81742,15942,15942,15934,20847,782
47,63637,234
41,733
34,46347,73747,78040,537
15,89935,482
10,738

0.64
0.75
0.72
0.63
0.49
0.86
0.84
0.29
0.15
0.02
0.05
0.93
0.95
0.97
0.75
0.85
0.41
0.37
0.23
0.88
0.68
0.58
0.52

(0.48)(0.43)(0.45)(0.48)(0.50)(0.35)(0.37)(0.45)(0.36)(0.14)(0.21)(0.26)(0.22)(0.17)(0.43)(0.36)(0.49)(0.48)(0.42)(0.32)(0.47)(0.49)(0.50)

0.57
0.69
0.68
0.58
0.53
0.83
0.81
0.24
0.20
0.03
0.08
0.87
0.89
0.95
0.69
0.79
0.41
0.41
0.26
0.86
0.58
0.51
0.36

(0.50)(0.46)(0.47)(0.49)(0.50)(0.38)(0.39)(0.43)(0.40)(0.17)(0.27)(0.34)(0.31)(0.21)(0.46)(0.41)(0.49)(0.49)(0.44)(0.35)(0.49)(0.50)(0.48)

Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, Vol.16, No.6, September 2020

15

Table 3-2. Basic statistics for attributes and attitude survey results according to school attendance support receipt status (Middle school)
Variable
3. Attributes and attitudes survey results
Consolidates material learnt in class in clear, personal manner: "very true" or "somewhat true"
Can proactively tackle even difficult matters: "very true" or "somewhat true""Checks" or "sometimes checks" unfamiliar words in a Japanese dictionary (including electronic dictionaries)"Thinks" or "usually thinks" of alternative solving methods for solved arithmetic/mathematics problems
FemaleGoing to school is "enjoyable" or "quite enjoyable"
School study/classes are "enjoyable" or "quite enjoyable"
Attends private tuition
Home-learning: doesn't know what or how to study
Home-learning: has no place to study
Home-learning: no one to help with study
Does homework properly: "very true" or "somewhat true""Definitely eats" or "mostly eats" breakfast every day
Brushes teeth morning and night: "very true" or "somewhat true"
Regular daily life, e.g. early to bed & early to rise: "very true" or "somewhat true"
Sleeps for at least eight hours during normal school time
Studies for at least one hour on weekdays
Usually plays videogames for at least 1.5 hours per day
Does not read a single book in a monthHas dreams and goals for adulthood: "very true" or "somewhat true"
Sees positive parts to self: "very true" or "somewhat true"
Proactively participates in local projects: "very true" or "somewhat true"
Member of a sports teamObs

Non-applicant
Mean Std. Dev.

40,07537,92637,90637,902
37,95537,67951,34851,29746,037
44,69644,88133,13351,35951,35140,03250,591
37,916
51,34951,36951,335
18,10937,925
13,391

0.61
0.67
0.56
0.53
0.48
0.82
0.61
0.53
0.43
0.02
0.08
0.91
0.95
0.99
0.61
0.45
0.61
0.43
0.28
0.77
0.63
0.37
0.62

(0.49)(0.47)(0.50)(0.50)(0.50)(0.38)(0.49)(0.50)(0.50)(0.15)(0.27)(0.28)(0.21)(0.10)(0.49)(0.50)(0.49)(0.49)(0.45)(0.42)(0.48)(0.48)(0.49)

School attendance support receipt status
Rejected applicant
School attendance support
Obs
Mean Std. Dev.
Obs
Mean Std. Dev.

Public assistanceObs
Mean Std. Dev.

4,517
4,403
5,106
5,110
5,131
4,300
6,118
6,116
5,345
5,147
5,190
3,650
6,118
6,120
4,507
6,047
5,105
6,118
6,123
6,117
2,457
4,403
1,776

2,958
2,680
2,620
2,616
2,577
2,739
3,628
3,628
3,221
3,098
3,136
2,482
3,634
3,625
2,944
3,531
2,617
3,625
3,631
3,624
1,134
2,679
  831

0.59
0.68
0.53
0.49
0.48
0.82
0.60
0.45
0.48
0.03
0.09
0.91
0.94
0.99
0.60
0.44
0.55
0.46
0.31
0.78
0.62
0.38
0.65

(0.49)(0.47)(0.50)(0.50)(0.50)(0.39)(0.49)(0.50)(0.50)(0.18)(0.29)(0.28)(0.24)(0.10)(0.49)(0.50)(0.50)(0.50)(0.46)(0.42)(0.48)(0.48)(0.48)

30,90827,74027,64827,642
27,65928,67938,041
37,99033,78832,59432,88825,91838,04938,05030,85037,37027,64438,04138,062
38,037
12,00527,740
9,120

0.56
0.64
0.52
0.47
0.49
0.80
0.57
0.36
0.50
0.03
0.12
0.88
0.92
0.99
0.58
0.46
0.50
0.48
0.30
0.78
0.59
0.36
0.58

(0.50)(0.48)(0.50)(0.50)(0.50)(0.40)(0.49)(0.48)(0.50)(0.18)(0.32)(0.33)(0.27)(0.11)(0.49)(0.50)(0.50)(0.50)(0.46)(0.42)(0.49)(0.48)(0.49)

0.51
0.58
0.50
0.42
0.51
0.76
0.55
0.27
0.56
0.06
0.18
0.79
0.85
0.98
0.54
0.43
0.46
0.53
0.31
0.77
0.52
0.33
0.47

(0.50)(0.49)(0.50)(0.49)(0.50)(0.43)(0.50)(0.44)(0.50)(0.24)(0.38)(0.41)(0.36)(0.13)(0.50)(0.50)(0.50)(0.50)(0.46)(0.42)(0.50)(0.47)(0.50)

Figure 2-1. Japanese standardized score: Grade and school attendance support receipt status(Source) Adachi Comprehensive Survey of Acquisition of Basic Academic Skills, 2010-2017

Figure 2-2. Mathematics standardized score: Grade and school attendance support receipt status(Source) Adachi Comprehensive Survey of Acquisition of Basic Academic Skills, 2010-2017

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NOGUCHI Haruko, BESSHO Shun-ichiro, USHIJIMA Koichi, KAWAMURA Akira, TANAKA Ryuichi / Public Policy Review

Figure 2-3. English standardized score: Grade and school attendance support receipt status(Source) Adachi Comprehensive Survey of Acquisition of Basic Academic Skills, 2010-2017

sleeps for at least eight hours during normal school time. Here, largely the same results wereobtained as with attitudes towards learning: groups that have not applied for school attendance support and pupils and students from households that were rejected applicants forschool attendance support tended to have more favorable lifestyle habits.

V-2.  Estimation results
V-2-1.  School attendance support status and academic performance, obesity,
home-learning conditions and everyday attitudes towards learning

Table 4 shows estimation results for equation (1). As defined in the previous section,school attendance support status is a proxy variable for household economic circumstance.
Accordingly, s00 (non-applicant → non-applicant), s11 (rejected applicant → rejected applicant), s22 (school attendance support → school attendance support), and s33 (public assistance → public assistance) imply no change in economic circumstances. Meanwhile, s01(non-applicant → rejected applicant), s02 (non-applicant → school attendance support), s03(non-applicant → public assistance), s12 (rejected applicant → school attendance support),s13 (rejected applicant → public assistance), and s23 (school attendance support → public assistance) signify a relative worsening in economic circumstances. Further, s10 (rejected applicant → non-applicant), s20 (school attendance support → non-applicant), s21 (school attendance support→ rejected applicant), s30 (public assistance → non-applicant), and s32 (public
assistance → school attendance support) are considered to imply improvement in economic
circumstances.
Now, taking s33 (public assistance → public assistance) as a reference, let us look at therelationship between the dependent variables and these changes in economic circumstance.
First, looking at cases of no change in economic circumstances (s00, s11, s22): for case s00,
considered to have the most favorable economic circumstances, the standardized score forJapanese is around 0.5 higher at a 5% significance level, the probability of private tuition at-

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Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, Vol.16, No.6, September 2020

Table 4. Estimation results: school attendance support status, academic performance and obesity,
home-learning conditions and everyday attitude towards learning (Fixed-effects model)(1)
Japanesestandardized
score

Definition of variableNon-applicant→Non-applicant(S00)

Non-applicant→Rejected applicant(S01)

Non-applicant→School attendance support(S02)

Non-applicant→Public assistance(S03)

Rejected applicant→Non-applicant(S10)

Rejected applicant→Rejected applicant(S11)

Rejected applicant→School attendance support(S12)

Rejected applicant→Public assistance(S13)

School attendance support→Non-applicant(S20)

School attendance support→Rejected applicant(S21)

School attendance support→School attendance support (S22)
School attendance support→Public assistance(S23)

Public assistance→Non-applicant(S30)

Public assistance→School attendance support(S32)

Constant
Observations
F test that all u_i=0
Prob>F
Durbin-Wu-Hausman test (Chai)
Prob>chi2
Number of ID_all

0.478**(0.233)0.384(0.251)0.415*(0.239)0.256(0.365)0.423*(0.245)0.460*(0.247)0.626**(0.264)-1.365(1.478)0.031(0.257)0.113(0.241)0.409*(0.224)-0.107(0.304)-0.163(0.438)0.500(0.313)49.216***(0.247)223,24510.9
0.000
1820.040
0.000
55,527(2)
Arithmetic/
mathematics
standardized
score
0.274
(0.229)0.343(0.246)0.259(0.235)-0.614(0.358)0.239(0.241)
0.190(0.243)0.499*(0.259)-1.302(1.452)-0.072(0.252)0.230(0.237)0.128(0.220)-0.009(0.299)-0.379(0.430)-0.114(0.308)49.473***(0.242)
223,24511.3
0.000
2045.930
0.000
55,527(3)
Englishstandardized
score

(4)
Rohrer’s
Index of 160
or higher(obese)

(5)
(6)
(7)
Rohrer’s
Private tuition Home
Index ofattendance
learning (nounder 100
one at home
(underweight)
to help withstudy)

0.363(0.745)0.495(0.771)0.593(0.738)0.545(0.851)0.655(0.748)0.619(0.756)0.788(0.764)0.567(2.661)1.077(0.757)0.760(0.731)0.878(0.710)-0.248(0.675)0.107(1.020)0.695(0.611)49.530***(0.713)-0.014(0.023)-0.012(0.023)-0.023(0.022)0.031(0.027)-0.014(0.023)-0.021(0.023)-0.012(0.023)-0.002(0.093)-0.006(0.023)-0.015(0.022)-0.009(0.022)0.009(0.020)0.031(0.028)0.020(0.021)
0.061***(0.022)0.021(0.023)0.015(0.023)0.014(0.022)
0.096***(0.027)0.015(0.023)0.011(0.023)0.012(0.023)0.001(0.093)0.017(0.023)0.006(0.023)0.002(0.022)0.003(0.020)-0.007(0.028)0.014(0.021)0.019(0.022)47,32711.13
0.000
390.7900.000
26,32360,8035.1
0.000
52.4200.000
36,64260,8033.08
0.000
29.9100.071
36,6420.046***(0.017)0.026(0.018)0.021(0.017)-0.010(0.026)0.027(0.018)0.023(0.018)0.019(0.019)-0.078(0.111)-0.016(0.018)0.036**(0.017)0.010(0.016)0.021(0.022)
0.053*(0.032)0.002(0.022)0.362***(0.018)
212,575
3.92
0.000
1206.260
0.000
55,264(8)(9)
ChecksThinks ofunfamiliar
alternative
words insolving
Japanese/
methods inkanjimathematics
dictionaries
problems-0.032***0.002
0.058**(0.009)(0.024)(0.029)-0.028***-0.0070.047(0.010)(0.025)(0.031)-0.021**-0.0130.054*(0.010)(0.024)(0.030)0.014-0.0390.064(0.015)(0.035)(0.043)-0.025**
0.011
0.048
(0.010)(0.024)(0.030)-0.012-0.0030.042(0.010)(0.025)(0.030)-0.023**0.024
0.066**(0.011)(0.026)(0.031)0.215***-0.109-0.009(0.066)(0.127)(0.151)-0.021**-0.0340.023(0.011)(0.025)(0.031)-0.011
0.008
0.052*(0.010)(0.024)(0.029)-0.017*0.009
0.051*(0.009)(0.023)(0.028)-0.025*0.045
0.049(0.013)(0.029)(0.035)0.011-0.059-0.027(0.018)(0.040)(0.051)
0.002
0.001
0.044
(0.013)(0.028)(0.033)0.077***
0.692***
0.579***(0.010)(0.023)(0.030)

194,0131.7
0.000
324.370
0.000
54,843

173,5022.27
0.000
2091.290
0.000
55,153130,933
2.28
0.000
141.0700.000
49,092Standard errors in parentheses*** p<0.01, ** p<0.05, * p<0.1
Gender dummy, school year dummy, and year dummy have been controlled for in all regression analysis

tendance increases by around 5 percentage points at a 1% significance level, and the proportion of affirmative responses to “thinks of alternative solving methods in mathematics problems” increases by 6 percentage points at a 5% significance level. Furthermore, ratio that
responded “there is no one at home to help with study” is 3 percentage points lower at a 1%
significance level. Meanwhile, for pupils and students that continue to be ineligible for provision of school attendance support expenses by local government despite having applied(s11), the standardized score for Japanese increased by around 0.5 at a 10% significance level, but no improvements were found in any other circumstances. In fact, whilst the statisticalsignificance level is not particularly robust at 10%, for pupils and students continuously receiving support from local government (s22) the standardized score for Japanese and the ratio of affirmative responses to “thinks of alternative solving methods in mathematics problems” tended to be higher, at around 0.4 points and 5 percentage points respectively, and theratio that responded “there is no one at home to help with study” is 2 percentage points lower.
Next, let us consider cases in which economic circumstances appear to have worsened.
First are cases of worsening from the state of not having applied school attendance support(s01, s02, s03). With s03, the greatest change in circumstances, the ratio of “underweight”

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NOGUCHI Haruko, BESSHO Shun-ichiro, USHIJIMA Koichi, KAWAMURA Akira, TANAKA Ryuichi / Public Policy Review

Rohrer’s Index of under 100 increases by 9.6 percentage points at a 1% significance level.
Meanwhile, with s01 and s02, the probability that “there is no one at home to help with study”
decreases by 2.8 and 2.1 percentage points, respectively. With s02, standardized scores forJapanese increase by 0.4 at a 10% significance level, and the ratio that responded “thinks ofalternative solving methods in mathematics problems” increases by 5.4 percentage points at
a 10% significance level. Looking now at changes from the state of rejected applicant (s12,s13): for pupils and students that changed from rejected applicant to school attendance support (s12), standardized scores for Japanese increased by around 0.6 at a 5% significance level, and standardized scores for arithmetic/mathematics increased by around 0.5 at a 10%
significance level. Additionally, with these pupils and students, the probability that “there isno one at home to help with study” decreases by 2 percentage points, and the ratio that responded “thinks of alternative solving methods in mathematics problems” also increased byaround 7 percentage points, at a 5% significance level. Meanwhile, for s13, in which economic circumstances have worsened considerably, whilst no statisticallysignificant differences in standardized scores were observed, standardized scores for Japanese and arithmetic/mathematics tended to be lower, and the probability that “there is no one at home to help
with study” decreased considerably by around 22 percentage points at a 1% significancelevel, implying greater difficulties in home-learning. Lastly, for cases of changes fromschool attendance support (s23), in the same manner as with s13, no statistically significant results were observed for standardized scores, but standardized scores for Japanese, arithmetic/mathematics and English all tended to be lower, and the probability that “there is no one
at home to help with study” decreases by around 3 percentage points at a 10% significancelevel.
Lastly, let us look at cases of improvement in economic circumstances. For improvement from rejected applicant (s10), standardized scores for Japanese increased by around 0.4
at a 10% significance level, and the probability that “there is no one at home to help withstudy” decreased by 3 percentage points at a 5% significance level. Next, looking at changes
from school attendance support (s20, s21): with s20, the probability that “there is no one athome to help with study” decreases by 2 percentage points at a 5% significance level. For
s21, though not measured with statistical significance, standardized scores tended to be higher in all academic subjects, the private tuition attendance rate increased by 4 percentage
points at a 5% significance level, and the proportion that responded with “thinks of alternative solving methods in mathematics problems” increased by around 5 percentage points at
a 10% significance level. For change from public assistance (s30, s32), although a great improvement in economic circumstances would be surmised with s30, the private tuition attendance rate may have increased by around 5 percentage points at a 10% significance rate, but
no other statistically significant relationship was observed.

V-2-2.   Physical capabilities and academic performance

Table 5 shows the results of equation (2) estimated for the whole sample, for girls, and forboys respectively. Let us first look at academic performance. Statistically significant positive

Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, Vol.16, No.6, September 2020

19

values were obtained for all standardized scores, except female scores in Japanese; accordingly, there is considered to be a positive correlation between physical capabilities and academic performance. Meanwhile, the dummy variable indicating obesity—i.e., a Rohrer’s Index of 160 or higher—had statistically significant negative values in all estimation formulas;
it is therefore highly likely that there is a negative correlation between physical capabilities
and obesity. Additionally, a positive correlation was observed between sports team membership and physical capabilities. However, no statistically significant correlation was observedwith the proxy variable for economic circumstances, i.e. school attendance support status.
Further, since the coefficients for academic performance, obesity and sports team membership—i.e., those which yielded statistically significant results—are more prominent formales than for females, there may be a gender difference in the correlations between thisgroup of variables and physical capabilities.

Table 5. Estimation results: physical capabilities and academic performance (fixed-effects model)
Definition of variable
Japanese standardized score
Arithmetic/mathematics standardized score
Rohrer’s Index 160 or higher (obese)
Member of sports team
Rejected applicant
School attendance support
Public assistanceConstant
Observations
R-squared
Number of ID_all

(1)
All

(2)
Female(3)Male0.021***(0.006)
0.059***(0.006)-1.902***(0.264)0.750***(0.089)-0.016(0.184)0.164(0.189)-0.235(0.563)41.046***(0.424)0.013(0.009)0.051***(0.009)-1.832***(0.358)0.621***(0.118)-0.040(0.247)0.064(0.256)0.044(0.684)42.591***(0.614)0.029***(0.008)0.065***(0.009)-2.280***(0.386)
0.789***(0.133)0.050(0.271)
0.317(0.277)-0.895(0.952)39.756***(0.584)

57,3820.054
35,56528,8730.045
17,74628,5090.079
17,819Standard errors in parentheses*** p<0.01, ** p<0.05, * p<0.1
Gender dummy, school year dummy, and year dummy have been controlled for in all regression analysis

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NOGUCHI Haruko, BESSHO Shun-ichiro, USHIJIMA Koichi, KAWAMURA Akira, TANAKA Ryuichi / Public Policy Review

VI.  Conclusion
In this paper, we performed quantitative analysis about the relationships between school
attendance support receipt status and academic performance and obesity, home-learning
conditions and everyday attitudes towards learning, and between physical capabilities andacademic performance. This analysis was conducted through simple fixed-effects models,
focusing on all pupils and students attending Adachi ward public elementary schools and junior high schools, and using panel data built by linking pupil/student name registers (list of
school-age children), information about application for and receipt of school attendance
support, and “The Survey on the Physical Capabilities of Pupils and Students,” and the “Adachi Comprehensive Survey of Acquisition of Basic Academic Skills” (conducted from second year of elementary school until third year of middle school), which was independently
conducted by Adachi ward in 2009–2017. Taking continuous beneficiaries of public assistance as a control group, and even having controlled for pupils’ and students’ fixed-effects,
the results of this analysis reveal that: with the shift considered to be the most extreme worsening of economic circumstances, namely from non-applicant to public assistance, the ratioof “underweight” children increases, and the academic performance and home-learning conditions of other groups tends to be better, suggesting the possibility that public assistancebeneficiary pupils and students are left in circumstances that are difficult in terms of learning. Pupils and students who receive school attendance support independently implemented
by municipalities are identified, with statistical significance, to be in better conditions interms of overall academic performance and home-learning compared to pupils and students
that are continuous beneficiaries of public assistance. Thus, the measures in question may beserving a certain function for pupils and students facing economic hardship. Regarding therelationship between academic performance and physical capabilities, it was revealed that,having controlled for pupils’ and students’ fixed-effects, there is a high probability that there
is a positive correlation between physical capabilities and academic performance, and a negative correlation with obesity.
There are many limitations to this paper, and many issues for the future. Firstly: the results in this paper are, ultimately, observations of “correlations”; any causal relations, including any mechanisms thereof, have yet to be distinguished and analyzed. Since the data
used in this paper is administrative data, it is difficult to control influence from unobserved
factors in household attributes such as family structure, and income, assets, education levels
and so forth. For example: with a shift from public assistance to school attendance support
non-applicant, where it would be expected that household economic circumstances haveprobably improved to a considerable degree, when little improvement is seen in academic
performance, home-learning conditions, everyday attitudes towards learning, and so forth,
there is thought to be influence from some unobservable factors. One possibility here is that,
following great changes in family structure and attributes due to, e.g., the parents’ divorce,the observed trends may be the result of a child’s circumstances being more affected by

Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, Vol.16, No.6, September 2020

21

these other such factors, rather than by economic improvements. Otherwise, it may be difficult for the attitudes and behaviors of the family or the child themselves to change, regardless of economic improvement, once they require public assistance. Additionally, further
analysis is needed regarding academic performance and physical capabilities, namely into:
why standardized scores, particularly standardized scores in arithmetic/mathematics show astatistically significant positive correlation with physical capabilities; whether there is any
causal relation between the two; and what sort of mechanisms are behind this phenomenon.
Second, and relatedly: since the results obtained in this paper cannot specify any causal
relations, it is difficult to clearly define policy implications regarding school attendance support, in particular. For example, the results show: a positive association between considerable worsening of a household’s economic circumstances (non-applicant → public assistance) and a child being “underweight”; and difficulties arising in home-learning conditions
for cases of rejected applicant → public assistance, but can specify no causality for either
phenomenon. The results are not robust in many areas: the statistical significance of correlations with school attendance support status, for instance, changes depending on academic
subject. Nonetheless, the results obtained by this study suggest the possibility that: school
attendance support measures by local government are serving a certain function for pupils
and students facing economic hardship; and it may be important that education conducted inpublic elementary and middle schools be well-balanced between both academic performance and physical capabilities.

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