OSIPP Discussion Paper: DP-2018-E-008

The Effects of Out-of-School Activities
in Elementary School Days on Future Income
May 7, 2018
Seira Suzuki*
PhD. Student, Osaka School of International Public Policy(OSIPP)【Key Word】Out-of-school activity, income, path analysis【JEL Classification】I24, Z10【Summery】This paper investigate the effect of out-of-school activity inelementary school days on one’s future income. In order to analyze

specifically, the model includes extra-curricular activities in junior highschool, years of schooling, marital status and occupation. They could beinfluenced by the activity and also have effects on income. The data used forthe analysis is the Preference Parameters Study. Related variables areextract and their relationship is calculated by path analysis. The result is incase of female, cultural activities have significant effect on income via

schooling. In case of male, educational and sports activities increase one’sfuture income.

* s-suzuki@osipp.osaka-u.ac.jp

I would like to appreciate Hisakazu Matsushige and Tsunehiro Otsuki of Osaka
University for their support. This research uses micro data from the PreferenceParameters Study of Osaka University’s 21st Century COE Program ‘Behavioral
Macrodynamics Based on Surveys and Experiments’ and its Global COE project‘Human Behavior and Socioeconomic Dynamics’. I acknowledge the program/project’s
contributors: Yoshiro Tsutsui, Fumio Ohtake, and Shinsuke Ikeda.

The Effects of Out-of-School Activities
in Elementary School Days on Future Income
Seira SUZUKI(Osaka School of International Public Policy, Osaka University)
1 - 31 Machikaneyama, Toyonaka, Osaka, Japan 560-0043
s-suzuki@osipp.osaka-u.ac.jp

1. Introduction
It is common for Japanese children to dedicate themselves to out-of-school activities such as dancing,playing sports and studying at cram schools. According to the research about the local educational power
conducted by Ministry of Education, Culture, Sports, Science and Technology (MEXT) in 2006, 70% of
elementary students experience some out-of-school activities on weekdays (MEXT, 2005). Nowadays, more andmore parents tend to let their children experience some activities after school. These activities are divided into
three categories: cultural experiences, sports experiences, and educational (specialized-school) experiences.
It is said that these activities are effective to one’s educational performance (Kataoka, 2015; Matsuoka,2017). However, since out-of-school activities are additional ones and not all children have opportunity to accessto it, it is unavoidable to create the difference between those who experience activities after school and those who
do not. Suppose that there is the tendency of reproduction as Shinogaya and Akabayashi (2012) indicates, thenout-of-school activities could work as an intermediary for the process. Once the impact of out-of-school activities
are measured, we can utilize the data and result with appropriate approach if necessary.
That is the motivation for this research. This paper is constituted of 5 sections: first, the next section reveals
the related past research and some points that remain to be solves, second, third section explain the data andmethod used for the analysis followed by the forth section indicating some major results and discussion, lastly,
fifth section conclude with the summary of this paper.

2．Objectives
So far, the effects of these activities have been analyzed separately, especially sports experiences (Umesaki,2004; Ohtake and Sasaki, 2009), and educational experiences (Naoi, 1978; Seiyama, 1981) were focused on. And
there are not many research that analyzed the effect of three types of activities together on one’s future outcomes.
There are two major reasons for it: first, there were no data about the situation of out-of-school activities until
recently, and second, cultural activities have not been regarded to be effective to nurture cognitive skill, which iscalculated by academic skills and so on. However, the effects of activities are well connected and because of therecent trend, many people experience the multiple activities in their childhood. In order for the appropriate
analysis, those three categories should be analyzed totally. Besides, cultural activities attract attention recently
because it could be recognized as means to nurture non-cognitive skills, which affect on performance on labormarket along with cognitive skills (Lee and Ohtake, 2014). This makes more important to include culturalactivities into analysis.
1Another important point of view to discuss this matter is gender. It influences the types of activities
experienced. So, the outcome should differ by gender. Furthermore, the process that effect of the out-of-school
activity appears on income should be also different. Now, no research has been conducted focusing on the effectof all the activities on one's future performances by gender.
In order to tackle with these problems, this thesis explores the two issues: 1 the effect of out-of-school
activities, considering the interaction between cultural activities, sports activities, and educational activities, on
one's labor productivities and 2 the difference of their effects by gender.

3. Analysis
The data used for this analysis is a part of Preference
Parameters Study conducted by Institute of Social andEconomic Research, Osaka University. The variables used
are as follows: family background, personal attribute,activities experienced during elementary school, activities
dedicated during junior high school, school year, job,marriage, and income. By dividing these variables into six
categories, it is allowed to analyze the direct and indirect
effects of out-of-school experience in elementary schooldays on income utilizing the path analysis. The conceptual
diagram is shown in Fig.1.
The analysis subjects are those aged from 35 till 55 in
2013. The questions in 2013 survey are mainly used for theanalysis. So, the data is individual cross-sectional data of2013 combined with questions with regard to one’s
attribution included in 2011 and 2012 survey.
As for the utilized variables, the first stage of Fig.1
includes living standard in age 15, parents' final academic
record, family with double-income, age, city size andnumber of siblings. In the second and third stage, thePaths focused on this study

Paths shown in previous studyFigure 1 Conceptual Diagram

activity related questions, the experience of out-of-school activities in elementary school days and the extra
activity engaged in junior high school days, are included. In the fourth stage, respondent’s years of schooling areused. Dummy variable ofmarriage and job status1 are created for the fifth stage. For the sixth stage, householdincome is used for the income variable. All the variables are described in Table 1 and statistical description isindicated in Table 2.
In order to verify the relationships between activities in elementary days and income as specific as possible,
Structural Equation Modeling (SEM) is applied to the analysis. SEM allows us to construct the model which is
not clear about the relationship of each variables. The model is created by first connecting all the variables, second
dropping the lines without significance. The goodness of the model is confirmed by Akaike Information Criteria(AIC)2.
1

The base category is people without any jobs.
AIC is used to check the goodness of the model. The equation of AIC is AIC= −2 lnL + 2k where lnL is themaximized log-likelihood of the model and k is the number of parameters estimated. This way, the smaller theAIC goes, the better the model becomes.
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Table 1 Variables and Description
Stage Variable1

Parents_School

LS15
Parents_DoubleSibling
City SizeAge
2

Elementary Activity

3

JH_team sports
JH_indivi sports
JH_group culture
JH_indivi culture

4

Schooling

5Marriage
Job

6

IncomeDescription
parents' final academic record
9=graduated junior high school;
12=graduated high school;
14=graduated college;
16=graduated university;
18=graduated master course;
20=graduated doctor course
living standard in age 15
11-scale numberfamily with double income
1=double income; 0=otherwise
number of siblings
sum of the number
city size in living area
2.5=living in town;
7=living in city under 100million citizens;
50=living in city over 100million citizens;
100=living in city over 1billion citizens;
age
from 35 till 55
category of experience of out-of-school activities in elemetary
school days
-no experience (base category)-only educational activities-only sports activities-only cultural activities-sports and cultural activities-sports and educational activities-cultural and educaitonal activities-all three types of activities
engaged in team sports in junior high school days
1=yes; 0=noengaged in individual sports in junior high school days
1=yes; 0=noengaged in cultural group activity in junior high school days
1=yes; 0=noengaged in individual cultural activity in junior high school days
1=yes; 0=no
final academic record
9=graduated junior high school;
12=graduated high school;
14=graduated college;
16=graduated university;
18=graduated master course;
20=graduated doctor course
marital status
1=being married; 0=otherwise
category of occupation-management-professional-white color (office and administrative support, sales, service)-blue color (construction, farming, fishing and forestry)-others (self employed)-housewives/ househusband
median of each category of household income(yen)50= less than 1 billion;
150= 1 billion to less than 2 billion;
300= 2 billion to less than 4 billion;
500= 4 billion to less than 6 billion;
700= 6 billion to less than 8 billion;
900= 8 billion to less than 10 billion;
1100= 10 billion to less than 12 billion;
1300= 12 billion to less than 14 billion;
1500= 14 billion to less than 16 billion;
1700= 16 billion to less than 18 billion;
1900= 18 billion to less than 20 billion;
2500= 20 billion and over3

Table 2 Statistical Description

Continuous data
Variables

Mean

Parents_School
LS15Sibling
City Size
Age
Schooling
IncomeSD

2.81
5.14
1.44
49.27
46.76
13.74
677.28

Min
1.56
1.80
0.81
35.80
5.55
1.85
378.76

Max

11001006
2.5
100
3555
921
50 3,000

Discrete data%

Variables

42.74
75.18

Male
Parents_Double
Elementary Activity
no experience (base)only educational activities
only sports activities
only cultural activities
sports and cultural activities
sports and educational activities
cultural and educaitonal activities
all three types of activities
Junior High Activity
JH_team sports
JH_indivi sports
JH_group culture
JH_indivi culture
Marriage
Jobmanagement
professional
white color
blue color
othershousewives/ househusband
N=1,261

11.90
5.55
7.45
22.52
9.60
6.66
19.35
16.97
46.07
26.49
17.37
15.23
0.84
10.47
16.73
43.30
9.60
7.22
9.99

4. Result and Discussion
First, let us go through the Figure 2 which indicates the result of female estimation. Following thesignificant path, we can understand the causal relationship of the model3. The unique point of the result is culturalexperience, cultural and sports experience, cultural and educational experience and all the experience inelementary school days increase the schooling with 1% significant. Also, as the school year extends, householdincome increases directly and indirectly. Moreover, these activities are affected by their background such as
parents schooling.
It is often pointed out the theory of reproduction. The theory is that the children from the family with higher
status will also end up with higher status. This result can be said that it reveals one of the reproduction processesof family via the activities in elementary school days.
One of the reasons why cultural activities are effective on school year is the idea of developing non3

All the result is available when requesting author.
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cognitive skills. Non-cognitive skill differs from cognitive skills which is calculated by exams. Instead, it is theskill that valued by communication, state of mind and so on. It is said that non-cognitive skill influences on one’sproductivities like cognitive skills. Cultural activities have been discussed to have influence on communitydevelopment. In this regard, it is possible that experiencing cultural activities nurture one’s non-cognitive skills.
Therefore, it has positive effect on schooling although it seems less effective than educational activities.

Figure 2 Path Diagram (Female)

Next, in the case of men from Figure 3, educational activities have a synergy with other activities affectdirectly management position which increase income. Also, experience of all the activities in the elementary
school days increase the school year along with income. The difference from female result is those activities are
not necessarily related to parents’ background.
Another interesting paths are sports experience in elementary school days. All the sports related experienceleads to the team sport in junior high school days. And the experience has a positive effect on marital status with5

1% significance. It is clear that experience of sports and educational activities in elementary school days increase
income in a step-by-step manner via schooling and occupation for male.

Figure 3 Path Diagram (Male)

What is different by gender is that the effect of cultural activities is clear for female, however, there is no
significant effect for male. In order to explain the reason behind the result is complex. Kataoka (2001) indicatesthe different role of cultural activities in young age between boys and girls. The cumulation of cultural capital forgirls plays an important role within the family. The research reveals that the cultural experience is influenced byfather’s social status. This is how the amount of cultural assets for his daughter works as an indicator of higher
social status. The tendency is only for girl’s case because the effects for boys did not appear clearly.

5. Conclusion
This paper analyzes the effect of cultural, sports and educational activities in elementary school days on
income using the nationwide data. It reveals not only direct effect but indirect effect via one’s academic process,occupation and marital status owing to path analysis method. As a result, in the case of female, cultural activities
6enhance one’s school year, which increase the household annual income. In the case of male, educational andsports activities plays an important role to enlarge the income.
There are still some points remain to be seen because of limitations of the data. The main question is how
large parents’ experience of activities impact on children. Previous study reveals that parents’ experience of
cultural activities affect their children’s experience, however, the effect is not included in this analysis becauseof the lack of variable. This point is expected to be revealed by the future study.
In conclusion, this result reveals the effect on the income differs by the types of activities in young age sothat those activities should be analyzed together. Moreover, the result implies the process of earning humancapital by experiencing some out-of-school activities, which are not always related with parental background.
However, this means the income gap between those who experience and who do not would increase. Therefore,
this paper supports the idea that it needs to find the way to equally distribute the opportunities of experiencing
various activities for young people.

Acknowledgement
This research uses micro data from the Preference Parameters Study of Osaka University’s 21st Century COE
Program ‘Behavioral Macrodynamics Based on Surveys and Experiments’ and its Global COE project ‘HumanBehavior and Socioeconomic Dynamics’. I acknowledge the program/project’s contributors: Yoshiro Tsutsui,Fumio Ohtake, and Shinsuke Ikeda.

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