1. The Role of Public University in Japan Reexamined: Have Public Universities Expanded Disadvantaged People’s Opportunity for University Education?
ISA RC28 Spring Meeting
May 27, 2016
National University of Singapore
Wataru NAKAZAWA
Graduate School of Human Sciences
Osaka University

2. Contents
Motivation
Research backgrounds and the current situation of higher education in Japan
Hypotheses
Method
Data
Results
Conclusion and Discussion

3. Motivation (1) Inequality in university education
Cultural or social capitals (Bourdieu and Passeron 1970)
School structures such as tracking (Oakes 1985; Gamoran 1986; Pallas et al. 1992)
Relative risk aversion (Breen and Goldthorpe 1997)
Reduction of Educational Inequality (Breen et al. 2009; Breen et al. 2010)
Tuition fees tend to increase because of the financial deficit in some industrial countries.

4. Motivation (2) Free tuition or decrease in tuition fees.
Scholarships or grants
Other financial supports
Removal of economic barrier
　　　・・・・・・
　⇒seem to secure equal educational opportunity.
We need to examine whether or not these policies progress to universities.

5. Motivation(3) On the other hand,
Positive correlation between SES and academic grades.
University applicants may concentrate on those universities that are relatively low costs because they want to avoid paying high costs.
⇒Those who have high academic grades may be advantageous to enroll in universities.
Thus, even if the private economic burden has been reduced, we cannot expect that a lower SES would progress to university. Rather, after all, a higher SES dominates among university applicants.

6. Figure 1. Share of Private Expenditure on Education 2012 (Source: OECD 2015 ChartB3.1)
Japan

7. Figure 2. Financial Support for socially Disadvantaged Students 2011 (Source: OECD 2015 ChartB5.3.)
Japan

8. Universities in Japan (as of 2015) Source: Basic Survey of Schools by MEXT

9. Figure 5. Changes of University Tuition Fees Sources: Annual Report of the Retail Price Survey (Major Items for Ku-area of Tokyo), and Annual Report on the Family Income and Expenditure Survey
The tuition fees of private universities always exceeded those of national (public) universities.
※　Bunkei （文系） includes humanity and social sciences.
Rikei （理系） includes natural sciences, engineering, agriculture, medicine, and pharmacy.

10. Figure 6. Changes of Household Burden on University Tuition Fees Sources: Annual Report of the Retail Price Survey (Major Items for Ku-area of Tokyo), and Annual Report on the Family Income and Expenditure Survey
This number implies the proportion of tuition fees relative to the average annual income of employees’ households.
The burden of tuition fees
Rikei private> Bunkei private> National
The burden has increased since the latter half of 1970s.

11. National Universities in Japan
Each prefecture has national universities.
Except for some famous universities which collect students from nationwide, national universities tend to collect local students.
Learning conditions (for example, low student-faculty ratio) are better than those in private universities.
Entrance examination: private universities demand 1～3subject(s)
national universities demand over 5 subjects
⇒Higher academic grades are required.
Higher prestige and trust among Japanese people.

12. Hypotheses
Those who had lower socioeconomic backgrounds were more likely to choose national universities.
National universities did not provide greater opportunities for university education for people with lower socioeconomic backgrounds in spite of lower tuition fees.

13. Method y selection = x1 + ν1 + ε1
Bivariate probit selection models
Selection equation (dependent variable: 1=university attendee, 0 = not university attendees)
Outcome equation (dependent variable:
1=national university, 0 = private university)
y selection = x1 + ν1 + ε1
y outcome = x2 + ν2 + ε2 , if y selection=1
x = independent variables, ν = unobserved heterogeneity, ε = random error
cor (ν1+ε1, ν2+ε2) = ρ

14. Data Social Stratification and Social Mobility (SSM)Survey
SSM1985 Men = 509
SSM1995 Men = 706, Women = 838
SSM2005 Men = 1,924, Women = 2,187
Japanese Life Course Panel Survey (JLPS)
Men = 1,576, Women = 1,715
Merged these four (three) datasets.
N(men)=4,715 N(women)=4,740
　 Born between
N(men, university attendees)=1,855
N(women, university attendees)=855

15. Independent Variables(1)
Socioeconomic backgrounds
Men (N=4715)
Women (N=4740)
Father's Occupation
Whole samples
Univ. attendee
EGP I + II (Service Class)
.228
.378
.214
.420
EGP IIIa (Routine non-manual)
.134
.184
.144
.208
EGP IVa+b (petty bourgeoisie)
.141
.113
.106
EGP V+VI (Skilled worker)
.093
.068
.066
EGP IIIb + VIIa (Non- , Semi –Skilled)
.203
.171
.211
.157
EGP IVc + VIIb (Agriculture)
.200
.086
.198
.043
Father's Education
Primary or Secondary
.791
.612
.782
.477
Tertiary
.209
.388
.219
.523

16. Independent Variables(2)
Residential areas
Men (N=4715)
Women (N=4740)
Whole samples
Univ. attendee
Hokkaido and Tohoku
.152
.115
.153
.094
Kanto (including Tokyo)
.255
.303
.254
.338
Chubu
.093
.081
.062
Tokai (including Nagoya)
.125
.120
.124
Kinki (including Osaka, Kyoto)
.140
.163
.136
.174
Chugoku and Shikoku
.104
.101
.110
.106
Kyushu
.131
.116
.130
.111

17. Independent Variables(3)
Control variables
Men (N=4715)
Women (N=4740)
Survey
Whole samples
Univ. attendee
SSM85
.108
.106 -
SSM95
.150
.121
.177
.102
SSM05
.408
.347
.461
.305
JLPS
.334
.427
.362
.593
Birth cohort
.180
.104
.153
.020
.192
.152
.175
.073
.148
.162
.135
.119
.281
.320
.308
.329
.199
.263
.230
.460

18. Independent Variables(4)
Instrumental variables
Specific variables of selection and outcome equations should be considered (Holm and Jæger 2011).
Men (N=4715)
Women (N=4740)
Whole samples
Univ. attendee
Range of Academic Grade
Middle and Low
.626
.377
.633
.276
High
.374
.623
.367
.724
High School Course
Vocational
.357
.167
.282
.157
Academic (General)
.556
.833
.629
.843
Did not go to high school
.088 -
.089

19. Results (1) Men Only probit coefficients of socioeconomic backgrounds Coefficients of cohort, residential areas, survey, grades, and high school courses are omitted
+ p<.10, * p<.05, ** p<.01, *** p< ρ = -.808
Simple Probit
Bivariate (Outcome)
Coef.
S.E.
Father's Occupation (vs. EGP I + II)
IIIa
.005
.097
.066
.085
IVa + b
-.089
.122
.238
.102 *
V + VI
-.165
.153
.222
.127 +
IIIb + VIIa
.128
.103
.394
.088
***
IVc + VIIb
.004
.133
.492
.110
Father's Education (vs. Primary or Secondary)
Tertiary Education
.136
.077
-.196
.069 **

20. Results (2) Women Only probit coefficients of socioeconomic backgrounds Coefficients of cohort, residential areas, survey, grades, and high school courses are omitted
+ p<.10, * p<.05, ** p<.01, *** p< ρ = -.655
Simple Probit
Bivariate (Outcome)
Coef.
S.E.
Father's Occupation (vs. EGP I + II)
IIIa
-.056
.139
.093
.124
IVa + b
.089
.175
.300
.156 +
V + VI
-.660
.272 *
-.271
.242
IIIb + VIIa
-.063
.159
.187
.143
IVc + VIIb
-.208
.266
.239
.236
Father's Education (vs. Primary or Secondary)
Tertiary Education
-.027
.113
-.293
.105 **

21. Conclusion
The first hypothesis, those who had lower socioeconomic backgrounds were more likely to choose national universities, was supported.
Recent changes may destroy the national university’s traditional role which provided more equal opportunity for tertiary education.

22. Discussion
Choice of instrumental variables in the bivariate probit selection models.
In the future, specialty(bunkei/rikei) should be considered.

23. Acknowledgement
I would like to thank the Research Committee of the SSM 2015 and JLPS for permitting me to obtain and use these data. This research was supported by Grants-in-Aid for Scientific Research (reference 15K04359) from the Japan Society for the Promotion of Science (JSPS).